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The two major themes of basic research in cognitive information science may be summarized, albeit inadequately, under two broad headings: research in the theory of information, and research in human information processes and intelligent algorithms. Theory of infomation While the understanding of the notion and nature of “information” remains elusive the School has pursued over the years consistently two lines of investigation concerned with, respectively, the foundations of language and the structure and meaning of signs. Both lines of investigation are characterized by our interest in the processing of signs by both natural processors and machines. Foundations of language. The School’s research in natural language foundations places a heavy emphasis on the role and structure of signs in natural language processes. The most significant advance in this area is the discovery of the intimate relation between the semantic structure of signs and the ostensive structure of language. The following account attempts to highlight some of the work in this area. An attempt was made to characterize mathematically some of the syntactic structure of the English noun phrase associated with semantic transformations that can be identified and hopefully measured. The motivation for this work was an attempt to model properties of the English demonstratives and articles and the quantifier “sum”. The research sucessfully sketched an algebra of functions for noun phrases and it obtained boolean algebras, product algebras, monadic algebras, or polyadic algebras. It was suggested that indexing, storage and retrieval facilities may be implemented with the structure of a product algebra. Evaluating the significance of these mathematical developments for theories of generative grammar, it was found that the base structure of the English noun phrase can be interpreted as a proto-sentence of an ordered pair of extensions in the form [USI, PSI, + Nl where US1 stands for a Universal Selective Index, PSI stands for a Particular Selective Index, and N stands for a common noun (Chiaraviglio and Gough, 1970). Continuing the development of the mathematics of ostension, an attempt was made to apply it to noun phrase relations (Gough and Chiaraviglio, 1970). Ostension of objects in the domain of interpretation of noun phrases was taken as the fundamental unit of analysis, and these ostensions were modeled by lexically bound or unbound primitive indexical markers, 1. Comparing the tasks accomplished by the resulting mathematics of noun phrase relations with the tasks accomplished by the mathematics of propositional functions, it was suggested that (a) propositional functions typically are used to analyze monadic and polyadic predication and quantification while noun phrase relations may be used to analyze noun phrases, a subclass of the class of terms; (b) both propositional functions and noun phrase relations relate items in the domain of interpretation of the language to items in the language; (c) it is possible to capture quantification and definite and indefinite terms by introducing complications on the algebra of propositional functions and it seems probable that the reverse procedure can be accomplished by starting with an algebra of noun phrase relations. Theories that appear open to study by noun phrase relations include derivation of quantifiers and interrogatives; internal structure of abstract noun phrases; modes of composition of terms; structures engendered by relative terms; and noun phrase relations whose domain includes sentences, phrases, and other parts of the language. Functional and relational algebras such as the algebra of noun phrase relations appear well suited to the study of a broad range of linguistic theories. “On the German Locative: A Study in Symbols” (Cough, 1967) represents a basic departure point for theoretical analyses of the foundations of natural language. Here, the structure of the element irgendwo is used to reveal the indexical symbolic nature of the locative adverbs of German and their symbolic relationships to each other as well as to the locative prepositional phrase. A representation of the notion of general to specific is established leading to the later development of both indexical logic and the mathematics of ostension. It is concluded that the structure of the internal grammar of certain form classes can be described in terms of a unique theoretical marker (called a “metaquantifier”); when this marker is incorporated into a generative grammar it assigns internal structure to locative strings in terms of grouping and dominance. The role of this same marker can be extended so that the tagmatics of locative
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strings can be translated into a semantic denotational formalization of inclusion. Grouping and dominance is thus transformed into a semantic formula that assigns denotata to the respective marker labeled locative groups and expresses the semantic inclusion relation existing between these groups and their respective denotata. The traditional semantic notion of general-tospecific ordering of locative elements is represented by marker inclusion. Quantification and inclusion combined with the expansion potential of the various adverbs should offer a basis for the classification of the adverbs themselves, a problem that has been the center of interest to many linguists. Finally, marker labeling provides some quantitative measure of locative information, since a locative string can be measured in terms of how many markers it contains. This theoretical analysis of the foundations of language progressively deepened insight into the nature of the semiotic process underlying the referential and the quantificational base of the English common-noun symbol and also the English noun phrase. The research suggests that the base structure of the English noun phrase is best interpreted as a proto sentential ostension. This interpretation levels out the multireferentiality and the multiquantificationality of the English common noun to an initial “sameness”. Generation of indefinite and definite reference, singular and plural, common and mass nouns is then accomplished by imposing the boolean operations of disjunction and/or conjunction on the base form. The determiners “a” and “the” then become symbols representing these semiotic processes. This research is characterized by the greater emphasis placed on understanding the symbolic nature of natural language. The focus is on three kinds of language signs: quantificational symbols, indexical symbols and general symbols (Gough, 1969; Gough, 1969a; Cough, 1970). A primitive marker that appears in the theory of all indexical symbols has been isolated: “I”, a concept roughly similar to that labeled by the word “this” in English, could provide a measure of indexical information in terms of the number and their depth of generation in any noun phrase (Cough, 1975). Identified with Duns Scotus’s concept of hecceity, the primitive indexical marker, combined with a primitive observation sentence and a mathematical treatment of ostension, can serve to reconstruct a primitive level of natural language and indicate what its semiotic nature would be (Cough, 1975a). Continuing efforts attempt to isolate the logical base of the sentential structure for all of natural language and, using a phenomenological approach, to identify the logical base of natural language with its semiotic structure; and to develop the base logos of language in terms of indexical symbolism. By carrying out this analysis at the unstructured and unnamed level of phenomenology, a base level of language can be developed without the constraints and the limitations of already given general terms and with no prior bias toward any sensory modality (Cough, 1976). The School’s research in the theory of formal language foundations stresses the role and structure of signs in logical structures and logical processes. The only work to be discussed in this section (Chiaraviglio, 1969) emphasizes the importance of the pragmatic dimension in logical and formal processes. By viewing pragmatics as an indexing and classification procedure which determines a relation of pragmatic synonymity or pragmatic equi-acceptability on a set of expressions of some language, we are able to model part of the pragmatic dimension of semiosis by a performance function 9 that maps the Cartesian product of a set of expressions 8, a set of conditions of valuation %?,a set of users 91, and a set of times of valuation 9 into the set of values 5’. The structure induced on 8 via B is the pragmatically ascertainable features of 8. The mapping B (or perhaps a family of such mappings) is specified only with respect to the known structures of the sets 8, Ce, 42, .Y and ‘If. By making several different realistic estimates of the structure of 9, we are able to conclude that (a) pragmatic significance is independent of collateral knowledge but dependent on analytic hypotheses; (b) the verification of a theory depends both on analytic hypotheses and collateral knowledge; (c) there is a pragmatic restriction on collateral knowledge since it must generate a similarity relation on the set of conditions that is a subrelation of compatibility; and (d) the set of allowable analytic hypotheses is also restricted pragmatically since the theoretical equivalence relation generated by these hypotheses and the null set of premises must be a subset of the pragmatically induced equivalence relation. Estimates of the structure of B involve the assumption that there are no privileged users or times of valuation for the sentences in 8’. When observing the results of abandoning such IPM Vol. 14 No. L-8
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restrictions we note that the range of the valuing functions will be sets of dispositions that are time, user, and condition dependent. In general, the valuing dispositions should depend on as many parameters as there are distinct types of collateral knowledge necessary to implement the valuing procedure. In every case the collateral knowledge is to be represented by a similarity relation on each of the set of entities on which the dispositions depend. The families of permissible similarity relations are selected pragmatically in the same fashion as they were selected for the set of conditions. However, the dependencies between pragmatic significance, pragmatic verification, collateral knowledge and analytic hypotheses remain unchanged. This research speculates that one of the marks of theoretical language is that it is devoid of tensed expressions, locatives and egocentric designators, and generally devoid of any parts of speech whose pragmatics depend on collateral knowledge about other parameters besides the conditions of valuation. Theory of signs. Semiotic research at the School of Information and Computer Science has included research into the structure and meaning of signs, and into sign processing investigations of perception, memory, learning, and decision making. An analysis of the School’s publications will show that this research has pioneered two new approaches to basic semiotics: experimental and theoretical. The emphasis in theoretical semiotics has been on the invention and explication of empirically testable concepts of sign structure, while emphasis in experimental semiotics has been on the development of instrumentation and experimental techniques for probing sign structure and thus leading to further theoretical explication. There is thus an intimate relation between the two approaches. A significant accomplishment of this research over the years is the development of an integrated and unified language for discussing the empirical aspects of meaning, information and sign structure. This in turn allows the refinement of vague and intuitive concepts in these areas into empirically testable concepts, the development of reliable, precise and valid instruments for the measurement of these concepts, and the development of experimental techniques for investigating the relations between these concepts. Thus explication and experiment have become interdependent, self-improving functions. The language is called the language of menetics (Pearson, 1977). The term originally stemmed from the “etics” of meaning. but the language has been found to be sufficiently general that it is now offered as an empirical language for much of semiotics and information science. In addition to presenting the language and describing its development, the work cited also gives examples of use of the language to discuss and analyze experimental results and to abduce theoretical results. A result of significance is an interpretation of Peirce’s system of signs in terms of an elementary prototheory of sign structure (Pearson and Slamecka, 1977a). The theory, called the Universal Sign Structure Model, argues that of the many taxonomies or classification schemes for signs, only the one proposed by Charles Peirce has proved to be satisfactory in every empirical setting or which a classification was wanted: and it shows how the applicability and usefulness of the Peircean scheme can be explained in terms of some very simple sign structure concepts. The theory is composed of a Universal Sign Structure Diagram, three principles, and nine representation theorems. The three principles are: The Representation Principle: A sign must consist of a trinary relation, and it must represent. A sign, therefore, consists of three parts: a syntactic structure, a semantic structure, and a pragmatic structure. The Principle of Internal/External Balance: The internal and the external structure of a sign must be balanced, consisting of exactly one internal component for each external component and vice versa. The internal components are called components of meaning. The external components are called information generators. The Principle of Additional Structure: Whenever a sign has more than the minimum structure, the additional structure is built up from the center out as per the Universal Sign Structure Diagram, and for each dimension independently. The application of the Universal Structure Model to understanding the foundations of information processes has been elaborated in several papers demonstrating the power of the semiotic approach for the development of empirical models of such information processes as
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those studied by researchers in psycholinguistics, information processing, communication theory, perceptual psychology and cognitive psychology. An integrated discussion and analysis is achieved and many suggestions for future work in experimental semiotics as related to communication can now be made (Pearson and Slamecka, 1977a; Slamecka and Pearson, 1978). Most of the instrumentation and experimental procedures and techniques developed in the SemLab are presented and described in the Proceedings of the 1976 Workshop on Experimental Semiotics. One of the fruitful marriages between theoretical explication and experimental development has been the invention of the eidometer to measure the deviation in the shape of artificial words from the “normal” shape of words for a given natural language. The recent results have led to suggestions for the refinement of the Miller-Bruner-Postman experiment for measuring information processing rates as a function of word shape, and for measuring Shannon’s redundancy curve for natural language (Pearson, 1978). Related research is directed toward the investigation of the quantitative relationships between the concepts of rank, frequency, word-types, and word-tokens for American English using a standard corpus of machine-readable text developed by Brown University and special software developed in the SemLab. Each of the equations proposed in the literature was tested against the entire corpus of a million words and most were found to be poor approximations of the observed results. Several equations were recommended for further testing and two new ones were suggested (Pearson, 1977a). The research employs automatic instrumentation for counting and measuring various aspects of basic sign phenomena; the instrumentation can also be applied to the observation and mathematical analysis of natural language (Flowers, 1976). Software programs have been written to count word-types and word-tokens in machine-readable natural language text, and producing rank-frequency distributions; perform the regression analysis of an observed distribution; observe and analyze linguistic and information structures; count polygrams in machine-readable text; use polygram frequency tables to produce artificial word shapes using Markov information sources of orders 0 through 3. The latter program represents the state of the art today in artificial word generation, and its latest version (producing artificial words of any finite Markov order) is a breakthrough in the state of the art of word generation. An entirely different kind of interaction between theory and experiment but regarding the concept of sign shape has led to a proposal to use the Kolmogorov potential as a measure of algorithmic information. This proposal is made in a historical and tutorial review paper that prepares the way for a semiotic explication of algorithmic information and eidontic complexity and their relation to sign shape (Pearson and Zunde, 1978). In line with the significance attributed to semiotic research, the School was active in the formation of a new scientific society, the Semiotic Society of America, and hosted the first annual conference of the Society in September 1976. The School was also active in establishing, within the SSA, a special interest group for empirical semiotics.
Human information processes and their algorithms The direction of research that has been taken by the School in the area of artificial intelligence may be divided into two main categories: the development of algorithms for “intelligent” performance, and the modeling of human information processes. These approaches are related in that the eventual goal of each is to describe or design computer programs and systems that exhibit behaviors and performances that are ordinarily associated with the human cognitive processes such as problem solving, game playing, object recognition, cognitive learning, information processing, and natural language understanding. They differ in the methodologies used to achieve this goal. Development of algorithms for intelligent performance. In designing programs for intelligent performance, the designer is primarily interested that his system succeed in performing the task that it was intended to accomplish. This performance-attainment strategy is known as the engineering approach. The processes used for achieving successful performance processes are usually related to the availability of technology and the principle of performance efficiency. Research conducted in the framework of the engineering approach during the last ten years
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at the School of Information and Computer Science may be classified into two main areas: machine vision and representation; and language understanding and speech recognition. In the area of machine vision the research emphasis has been on automatic picture analysis and object recognition (Baird, 1972; Baird and Kelly, 1974; Grosky and Wang, 1975). One research effort (Baird, 1972) led to the development of a new paradigm for picture recognition such that contextual information could be explicitly utilized leading to recognition performance that implicitly uses intensional class descriptions. More specifically, the paradigm relies on a procedure whereby the “semantics” of a picture or sensory information is provided. In addition, a set of rules of inference is developed. This set acts on a scene description resulting in the generation or “discovery” of new properties and relations. Subsequently a simplified and more limited version of the “semantic” paradigm was reported on. A new technique was introduced and described for recognizing objects in digitized gray level pictures, based on (a) the use of a preprocessing procedure for determining the existence of “primitive” properties and relations which hold for or between objects in a picture; (b) the succinct and explicit representation, in the form of “rules of inference” of the relational structure of the objects or scenes to be analyzed; and (c) the unique application of the rules to a sequence of thresholded versions of the input picture. The technique was illustrated in the recognition of facial features. The overall objective of the School’s research in machine vision has been the development of computer representation for pictorial concepts. A primary goal of this work was to develop a method for representing pictures in computers based on types of vertices and connectivity of vertices; and to describe pictorial concepts in terms of this representation method for purposes of recognition. In the area of computational language analysis, an interesting contribution has been made on the systematic decomposition and automatic recomposition of Chinese ideograms by means of computational techniques (Ting and Horng, 1975). The principal concepts associated with the techniques are: (a) a decomposition procedure used to create a pseudo-alphabet for uniquely representing most Chinese characters; (b) the existence of natural character writing sequences that may conveniently be adapted in conjunction with the proposed alphabetic set for input; and (c) the existence of a set of identifiable structured relationships among the sub-components which may be employed within the computational systems for automatic recomposition. A two-step process was employed for the recomposition procedure. The first step converts the alphabetic string into an intermediate sub-character string. In the second step, the natural structured characteristics are then analyzed to obtain the transformational vectors and control indicators, and these vectors and indicators are used in the recomposition process. Research in this area is still current. Presently, the associated rules, parameters and proposed alphabet and sub-character sets are being refined. The modeling of human information processes. The computer modeling of human information processes is essentially the casting of psychological and information processing theories, hypotheses, and models in terms of formal algorithms and computer programs. This approach is largely empirical and presupposes systematic inquiry in the area of human information processing. There are two empirical problems associated with this approach: one has to do with identifying and applying reliable techniques to collect data on information processing behaviors that may be used in developing computer models; the other is that of constructing appropriate measures for the validation of algorithmic models and hypotheses. The School’s research in this area has dealt with various aspects of these methodological problems. The focus has been on two key issues: (1) strategies for information acquisition, and (2) problem solving and strategies for representation. In the area of strategies for information acquisition, one emphasis has been on the development of semantic information measures to assess the status of information flow between the subject and an information source as defined by a well-structured set of experimental conditions (Coulter, 1974; Coulter and Siegmann, 1974; Siegmann et al., 1974). In traditional experiments requiring information acquisition (e.g. learning and concept formation), trials are presented in a fixed or random order. This procedure allows the subject little or no opportunity to control the sequence of communication events and thereby restricts the range of behaviors displayed. Such procedures limit the subject’s information acquisition
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strategies. As a result, conclusions drawn from traditional experiments may seriously underestimate the importance of subject-directed activities in acquiring information and may present a distorted picture of human information processing. Alternatively, the School’s aim has been to develop a linguistically oriented methodology for conducting experiments in which the subject may play an active role in a dialogue or conversation on a trial by trial basis. In a related project the researchers conducted a dialogue experiment using rote material which led to the development of a model for human information acquisition strategies. The model was designed to (a) account for strategy differences induced by instructional set; (b) describe individual differences in strategies; and (c) incorporate and predict previous results of human scanning processes. The model is based on semantic information measures that are employed to describe information transfer in the dialogue experiments. A computer program on these measures calculates the theoretical information state of subjects at each response state. These calculations, along with corresponding plots produced by the program, allow a quantitative analysis of different learning strategies. Another direction of research on human information acquisition investigated factors that were conjectured to affect human indexing performance. In a related work, a measure of indexing consistency based on the concept of a fuzzy set was developed. Both projects are described in Chapter III. In the area of problem solving, the main emphases have been on the question of problem formulation and problem representation (Badre and Starks, 1973; Badre, 1974; Badre and Slamecka, 1976; Kochen and Badre, 1974). The term problem formulation refers to the process of generating a specific problem statement that permits a solution to a given problem. When the initial presentation lacks the necessary and sufficient information to find a solution, then it is said that the problem statement is ill-defined or incomplete. When a problem solver is given an incomplete problem statement, he must move to reformulate the statement by specifying the missing information. This process of having to reformulate the problem statement makes it necessary for the problem solver to shift his representation of the problem. It is on the question of shifts of representation that new contributions have been made. Let representation R(t) and a given time be defined as a fourtuple L(t), H(t), B(t), F(t) such that L(t) is an internal processing language specified by terminal and non-terminal vocabulary denoting constants and variables; H(t) is a set of hypotheses, its members well-formed i = 1,. . . , n, sentences, H,, . . . Ii,, and with Hi is associated a weight wi(t) and a saliency, ai( where n equals the number of salient hypotheses; B(t) is a data base associated with a system of interpretation and consisting of a set of elements in a universe of discourse which can be compared to observed states of the external environment; F(t) is a set of operators. This property of a representation allows the transfer from one hypothesis to another. A shift of representation is said to occur if L(t,) z L(t,) or H(t,) # H(t,) or B(t,) z I or F(t,) # F(t,). Shifts in H(t) are characterized by changes in weight and saliency of hypotheses. The saliency of an hypothesis, ai( takes only the values 0 or 1. The reason is that an hypothesis is either being entertained and therefore in salient storage with value 1, or not being considered and thus in insalient storage with value 0. When an hypothesis is retrieved from insalient to salient storage then a saliency shift of representation has occurred. Hence, every time a new hypothesis is tested, it is assumed that a saliency shift has taken place. A new hypothesis is defined as the first test-occurrence of an hypothesis. The testing of an hypothesis is a function of the weight assigned those hypotheses in salient storage. If the only change that occurs before testing is a reassignment of weights, then this is called a weight shift. It is assumed here that the key processing feature of insight problem-solving is the saliency shifting representations. It can be argued that shifts in B(t) constitute saliency shifts since new hypotheses necessarily accompany change in data-base (Badre, 1974). Based on the above definition of a shift of representation, it has been confirmed (Kochen and Badre, 1974, 1976) that for a class of permutation problems the acquisition of representations is (1) a function of (a) what is contained in the statement of the problem, and (b) the experience of the problem solver; and (2) different in process between problems that are ill-defined and those that are well-defined. In addition to this confirmation, the researchers have
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proposed and tested a way to measure the quality of question-protocols as indicative of problem solving performance. The long range objective of research on problem solving at the School of Information and Computer Science is to better understand the information processes that lead to the formulation of principles for developing algorithms and computer systems that model expert problem solving of ill-defined problems. In a separate line of research, a generalized symbolic model of man-machine interactions has been described (Ting and Badre, 1975. 1976). The model was intended to represent the man-machine interactive behaviors of interactive adaptive logic systems. The use of the model was demonstrated by its application to an on-line audiographic learning facility (Slamecka, 1973) with emphasis on a pre-selected set of interactive functions. The more fundamental research effort, summarized in this section, has, at least in some instances, preceded and contributed to the design of experimental systems which are intended to aid humans in the performance of “intelligent” operations. The latter systems are described in Chapter III of this review. REFERENCES shifting on the solving of insight problems. In Information Proc. of the 37th America1 Society for Information Science Annual Meeting, Atlanta,
Badre, A. N. (1974). The effects of hypothesis Utilities:
Georgia. Badre, A. N. and Slamecka, V. (1976). Problem-solving approaches to clinical decision processing. Biosci. Commun. 2, 269-281. Badre, A. N. and Sharks, D. D. (1973). Concept learning as a function ability and method. In Proc. of the American Psychological Association, Montreal. Baird, M. L. (1972). A. Paradigm for Semantic Picture Recognition. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Baird, M. L. and Kelly, M. D. (1974). Recognizing objects by rules of inference on sequentially threshold Gray-level pictures. Research Rep. GMR-1436. Computer Science Department, General Motors Corporation Research Laboratories, Warren, Michigan. Baird, M. and Kelly, M. D. (1974). A paradigm for semantic picture recognition. Pattern Recognition 6, 61-74. Chiaraviglio, L. (1969). Performance, collateral knowledge and analytic hypothesis. L’age de /a Science I, 9-20. Chiaraviglio, L. and Gough, J., Jr. (1970). Towards a syntax-monitored semantic pattern recognition. In Progress of Cybernetics: Proc. of the Int. Congress of Cybernetics (Ed. by J. Rose), Vol. III. Gordon & Breach, London. Coulter, N. S. (1974). A Human Information Acquisition Model Based on Dialog Experimentation Which Incorporates Display Eflects. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Coulter, N. S. and Siegmann, P. J. (1974). Acquisition strategies revealed by dialog experimentation. In Information Utilities: Proc. of the 37th America1 Society for Information Science Annual Meeting, Atlanta, Georgia. Dexter, M. E. (1972). A Study of Information Control in Computer-Aided Instruction. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Plowers, J. (1976). Progress in semiotic software at Georgia Tech’s SemLab. Semiotic Scene 1. Gough, J., Jr. (1967). On the German locative-a study in symbols. Mech. Transl. 10,68-83. Gough, J., Jr. (1969). Papers on the English determiners and the base structure of the English noun phrase. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1969a). The syntax-based semantics of the English determiners “O”, “A” and “THE”. Papers in Linguistics 1, 414. Gough, J., Jr. (1970). A semiotic base for grammar. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1975). The primitive semiotic role of indexical symbolism. In Research 197C75:Annual Progress Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1975a). Man’s primal language. In Proc. of the 5th Int. Congress of Logic, Methodology and Philosophy of Science, London, Canada.
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Gough, J.. Jr. (1976). A primitive phenomenological semiotic paradigm for language. In Proc. of the 1976 Annual Conf. of the Semiotic Society of America, Atlanta, Georgia. Cough, J., Jr., Burrows, W. S., Roehrkasse, R. C. and Herbster, R. E. (1%8). Analysis of verb tense in scientific articles. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. and Chiaraviglio, L. (1970). On the base referential structure of the English noun phrase. Foundations of Language 6,447-462. Gough, J., Jr. and Valach, M. (1974). Indexical symbolism: a primitive semiotic system. In Information Utilities: Proc. of the 37th Annual Meeting of the American Society of Information Science, Atlanta, Georgia. Grosky, W. and Wang, S. (1975). A language for two-dimensional digital picture processing. In Proc. of the Association for Computing Machinery Special Interest Group for Programming Languages/Special Interest Group for Computer Graphics-Hotida Int. University Symp. on Graphic Languages, Miami, Florida. Hawkey, R. L. (1%8). Some representational functions of writing systems. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Hawkey, R. L. (1%9). Towards a Descriptive Apparatus for the Synchronic Analysis of Writing Systems. Ph.D. Thesis. Vanderbilt University, Nashville, Tennessee. Hawkey, R. L. (1971). A critique of certain basic notions in Chomsky’s Syntactic Structures. Folia Linguistica 4, 193-209. Kochen, M. and Badre, A. N. (1974). On the precision of adjectives which denote fuzzy sets. J. Cybernetics 4, 49-59. Kochen, M. and Badre, A. N. (1974). Questions and shifts of representation in problem-solving. Am. J. Psychol. 81, 369-383. Kochen, M., Badre, A. N. and Badre, B. (1976). On recognizing and formulating mathematical problems. J. Instruct. Sci. 5, 115-131. Pearson, C. (1975). Lab Manual for Semiotics. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (1976a). Communication Processes. Mimeographed course notes. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (1977). Towards an Empirical Foundation of Meaning. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (Ed.) (1977a). Proc. of the 1976 Annual Conference of the Semiotic Society of America, Atlanta, Georgia. Pearson, C. (1978). Review of Information and Structure by Garner, W. P. Computing Rev. Feb. 1978. Pearson, C. (1978). An objective concept of “word shape” for natural language. (To appear in the Proc. of the 1977 Annual Conf. of the Semiotic Society of America, Denver, Colorado.) Pearson, C. and Slamecka, V. (1974). Semiotic foundations of information science. In Research 1973-74: Annual Progress Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1975). Semiotic foundations of information science. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1976). Semiotic foundations of information science. Research Rep. School of Information Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1977). A theory of sign structure. Bull. Semiotic Sot. Am. l(2), l-22. Pearson, C. and Slamecka, V. (1977a). Semiotic foundations of information science. Research Rep. School of Information Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1978). Review of experimental work in semiotics. (To appear in Progress in the Communication Sciences 1.) Pearson, C., Slamecka, V., Zunde, P., Flowers, J., Betts, R., Shin, K. J. and Canyas, D. (1975). Semiotic foundations of information science. In Research 1974-75: Annual Progress Rep. School of Znformation and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Zunde, P. (1978). The Kolmogorov potential as a measure of algorithmic information. (To appear in Int. Z. Comput. Inform. Sci.) Rogers, D. E. (1964). Context-sensitivity in the verbal root set of Panini’s grammar. In Towards Tomorrow’s Linguistics (Ed. by R. W. Shuy and C. J. N. Barley). Georgetown University Press, Washington D.C. Siegmann, P. J., Coulter, N. S. and Stapleton, M. S. (1974). Methodology utilizing semantic information measures for dialogue experiments. In Information Utilities: Proc. of the 37th American Society for Information Science Annual Meeting, Atlanta, Georgia.
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Slamecka, V. (1%6). Principles of substantive analysis of information. In Proc. of the 1965 Congress of the ht. Federation for Documentation, pp. 22!IL234. Spartan Books, Washington. Slamecka, V. (1973). An audiographic system for self-instruction. J. Am. Sot. Injorm. Sci. 24, 405415. Slamecka, V. and Pearson, C. (1975). Information science. In Encyclopedia of Computer Science (Ed. by A. Ralston and C. L. Meek). Petrocelli/Charter, New York. Slamecka, V. and Pearson, C. (1978). The portent of signs and symbols. In The Many Faces of Information Science (Ed. by E. Weiss), pp. 105-126. Westview Press, Boulder, Colorado. Stapleton, M. L. (1974). A Methodology Utilizing Semantic Information Measures for Conversational or Dialogue Experiments. Ph.D. Thesis. School of Information and Computer Science. Georgia Institute of Technology, Atlanta, Georgia. Ting, T. C. and Badre, A. N. (1975). Modelingco-adaptive man-machine interactive systems. In Proc. of the 1975 Southeastern Conj. of the Society for General Systems Research, Athens, Georgia. Ting, T. C. and Badre, A. N. (1976). Dynamic model of man-machine interactions: design and application with an audiographic learning facility. J. Man-machine Studies 8, 75-88. Ting. T. C. and Horng, C. S. (1975). Graphemic analysis and synthesis of Chinese ideograms. In Proc. of the 1975 Computer Science, Washington, D.C. Ting, T. C. and Horng, C. S. (1975a). Toward a systematic decomposition and automatic recomposition of Chinese ideographs. In Proc. of the 1975 Int. Computer Symp., Taipei, Republic of China. Valach, M. (1970). A Q-graph approach to parsing. In Proc. of the Conf. on Linguistics, University of Iowa. Winner, R. I. (1973). Cartoons: an initial investigation of animated graphs. In Proc. of the 1973 Annual Nat. Conf. of the ACM, Atlanta, Georgia. Zunde, P. (Ed.) (1974). Information Utilities: Proc. of the 37th Annual Meeting of the American Society of lnjormation Science, Atlanta, Georgia. Zunde. P. and Dexter, M. E. (1%8). Statistical models of index vocabularies. In J. Am. Sot. Inform. Sci. 5, 73-78.
3.
THEORY OF COMPUTATON
The School of Information and Computer Science has pursued an active program of research in theoretical computer science since 1968. The general orientation of its research program is metatheoretical-concerned more with unifying principles than with specific problems-and the directions taken by its researchers in the theory of computing have their basis in this milieu. Given this non-standard backdrop, the main lines of research at the School have paralleled national research interests; in several instances, however, our research results pre-date trends which later appear in the general literature. The specific contributions of the School’s researchers will be discussed under the following broad categories: (1) automata, forma1 languages, algorithms, complexity; (2) applications of logic to computer science; (3) new models of computation; and (4) current trends.
Automata, formal languages,
algorithms, complexity
Considerable development of the theory of systems of automata, arrayed in geometrical fashions, has taken place at the School between 1968 and 1976. One class of problems successfully addressed is the relationship between parallel and sequential nodes of operation of cellular arrays. An especially attractive by-product of these results is the ability to prove results concerning the processing of n-dimensional patterns (n 2 2). For definitions, let us consider a genera1 tessellation mode1 consisting of a countable set of uniform finite-state machines which are interconnected in some fashion which can be specified by a local neighborhood structure. Given the state of a machine M; and its neighbors N;, . . . , Nk, a local transformation determines the next state of Mi as a function of the k + 1 “local” states. A configuration of a tessellation automaton is defined by state description of the component machines. Parallel transformations update the configurations as follows: the state machine in a successor configuration of c is a function of the k + 1 states in configuration C* which differs from c only in that the states of all cells processed before c have been updated. Tessellation automaton TA simulates automaton TAT in (t/q) real-time if configurations reachable by q transformations in TA are reachable in at most t transformations in TA2. In (Grosky
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SCIENCE
The two major themes of basic research in cognitive information science may be summarized, albeit inadequately, under two broad headings: research in the theory of information, and research in human information processes and intelligent algorithms. Theory of infomation While the understanding of the notion and nature of “information” remains elusive the School has pursued over the years consistently two lines of investigation concerned with, respectively, the foundations of language and the structure and meaning of signs. Both lines of investigation are characterized by our interest in the processing of signs by both natural processors and machines. Foundations of language. The School’s research in natural language foundations places a heavy emphasis on the role and structure of signs in natural language processes. The most significant advance in this area is the discovery of the intimate relation between the semantic structure of signs and the ostensive structure of language. The following account attempts to highlight some of the work in this area. An attempt was made to characterize mathematically some of the syntactic structure of the English noun phrase associated with semantic transformations that can be identified and hopefully measured. The motivation for this work was an attempt to model properties of the English demonstratives and articles and the quantifier “sum”. The research sucessfully sketched an algebra of functions for noun phrases and it obtained boolean algebras, product algebras, monadic algebras, or polyadic algebras. It was suggested that indexing, storage and retrieval facilities may be implemented with the structure of a product algebra. Evaluating the significance of these mathematical developments for theories of generative grammar, it was found that the base structure of the English noun phrase can be interpreted as a proto-sentence of an ordered pair of extensions in the form [USI, PSI, + Nl where US1 stands for a Universal Selective Index, PSI stands for a Particular Selective Index, and N stands for a common noun (Chiaraviglio and Gough, 1970). Continuing the development of the mathematics of ostension, an attempt was made to apply it to noun phrase relations (Gough and Chiaraviglio, 1970). Ostension of objects in the domain of interpretation of noun phrases was taken as the fundamental unit of analysis, and these ostensions were modeled by lexically bound or unbound primitive indexical markers, 1. Comparing the tasks accomplished by the resulting mathematics of noun phrase relations with the tasks accomplished by the mathematics of propositional functions, it was suggested that (a) propositional functions typically are used to analyze monadic and polyadic predication and quantification while noun phrase relations may be used to analyze noun phrases, a subclass of the class of terms; (b) both propositional functions and noun phrase relations relate items in the domain of interpretation of the language to items in the language; (c) it is possible to capture quantification and definite and indefinite terms by introducing complications on the algebra of propositional functions and it seems probable that the reverse procedure can be accomplished by starting with an algebra of noun phrase relations. Theories that appear open to study by noun phrase relations include derivation of quantifiers and interrogatives; internal structure of abstract noun phrases; modes of composition of terms; structures engendered by relative terms; and noun phrase relations whose domain includes sentences, phrases, and other parts of the language. Functional and relational algebras such as the algebra of noun phrase relations appear well suited to the study of a broad range of linguistic theories. “On the German Locative: A Study in Symbols” (Cough, 1967) represents a basic departure point for theoretical analyses of the foundations of natural language. Here, the structure of the element irgendwo is used to reveal the indexical symbolic nature of the locative adverbs of German and their symbolic relationships to each other as well as to the locative prepositional phrase. A representation of the notion of general to specific is established leading to the later development of both indexical logic and the mathematics of ostension. It is concluded that the structure of the internal grammar of certain form classes can be described in terms of a unique theoretical marker (called a “metaquantifier”); when this marker is incorporated into a generative grammar it assigns internal structure to locative strings in terms of grouping and dominance. The role of this same marker can be extended so that the tagmatics of locative
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strings can be translated into a semantic denotational formalization of inclusion. Grouping and dominance is thus transformed into a semantic formula that assigns denotata to the respective marker labeled locative groups and expresses the semantic inclusion relation existing between these groups and their respective denotata. The traditional semantic notion of general-tospecific ordering of locative elements is represented by marker inclusion. Quantification and inclusion combined with the expansion potential of the various adverbs should offer a basis for the classification of the adverbs themselves, a problem that has been the center of interest to many linguists. Finally, marker labeling provides some quantitative measure of locative information, since a locative string can be measured in terms of how many markers it contains. This theoretical analysis of the foundations of language progressively deepened insight into the nature of the semiotic process underlying the referential and the quantificational base of the English common-noun symbol and also the English noun phrase. The research suggests that the base structure of the English noun phrase is best interpreted as a proto sentential ostension. This interpretation levels out the multireferentiality and the multiquantificationality of the English common noun to an initial “sameness”. Generation of indefinite and definite reference, singular and plural, common and mass nouns is then accomplished by imposing the boolean operations of disjunction and/or conjunction on the base form. The determiners “a” and “the” then become symbols representing these semiotic processes. This research is characterized by the greater emphasis placed on understanding the symbolic nature of natural language. The focus is on three kinds of language signs: quantificational symbols, indexical symbols and general symbols (Gough, 1969; Gough, 1969a; Cough, 1970). A primitive marker that appears in the theory of all indexical symbols has been isolated: “I”, a concept roughly similar to that labeled by the word “this” in English, could provide a measure of indexical information in terms of the number and their depth of generation in any noun phrase (Cough, 1975). Identified with Duns Scotus’s concept of hecceity, the primitive indexical marker, combined with a primitive observation sentence and a mathematical treatment of ostension, can serve to reconstruct a primitive level of natural language and indicate what its semiotic nature would be (Cough, 1975a). Continuing efforts attempt to isolate the logical base of the sentential structure for all of natural language and, using a phenomenological approach, to identify the logical base of natural language with its semiotic structure; and to develop the base logos of language in terms of indexical symbolism. By carrying out this analysis at the unstructured and unnamed level of phenomenology, a base level of language can be developed without the constraints and the limitations of already given general terms and with no prior bias toward any sensory modality (Cough, 1976). The School’s research in the theory of formal language foundations stresses the role and structure of signs in logical structures and logical processes. The only work to be discussed in this section (Chiaraviglio, 1969) emphasizes the importance of the pragmatic dimension in logical and formal processes. By viewing pragmatics as an indexing and classification procedure which determines a relation of pragmatic synonymity or pragmatic equi-acceptability on a set of expressions of some language, we are able to model part of the pragmatic dimension of semiosis by a performance function 9 that maps the Cartesian product of a set of expressions 8, a set of conditions of valuation %?,a set of users 91, and a set of times of valuation 9 into the set of values 5’. The structure induced on 8 via B is the pragmatically ascertainable features of 8. The mapping B (or perhaps a family of such mappings) is specified only with respect to the known structures of the sets 8, Ce, 42, .Y and ‘If. By making several different realistic estimates of the structure of 9, we are able to conclude that (a) pragmatic significance is independent of collateral knowledge but dependent on analytic hypotheses; (b) the verification of a theory depends both on analytic hypotheses and collateral knowledge; (c) there is a pragmatic restriction on collateral knowledge since it must generate a similarity relation on the set of conditions that is a subrelation of compatibility; and (d) the set of allowable analytic hypotheses is also restricted pragmatically since the theoretical equivalence relation generated by these hypotheses and the null set of premises must be a subset of the pragmatically induced equivalence relation. Estimates of the structure of B involve the assumption that there are no privileged users or times of valuation for the sentences in 8’. When observing the results of abandoning such IPM Vol. 14 No. L-8
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restrictions we note that the range of the valuing functions will be sets of dispositions that are time, user, and condition dependent. In general, the valuing dispositions should depend on as many parameters as there are distinct types of collateral knowledge necessary to implement the valuing procedure. In every case the collateral knowledge is to be represented by a similarity relation on each of the set of entities on which the dispositions depend. The families of permissible similarity relations are selected pragmatically in the same fashion as they were selected for the set of conditions. However, the dependencies between pragmatic significance, pragmatic verification, collateral knowledge and analytic hypotheses remain unchanged. This research speculates that one of the marks of theoretical language is that it is devoid of tensed expressions, locatives and egocentric designators, and generally devoid of any parts of speech whose pragmatics depend on collateral knowledge about other parameters besides the conditions of valuation. Theory of signs. Semiotic research at the School of Information and Computer Science has included research into the structure and meaning of signs, and into sign processing investigations of perception, memory, learning, and decision making. An analysis of the School’s publications will show that this research has pioneered two new approaches to basic semiotics: experimental and theoretical. The emphasis in theoretical semiotics has been on the invention and explication of empirically testable concepts of sign structure, while emphasis in experimental semiotics has been on the development of instrumentation and experimental techniques for probing sign structure and thus leading to further theoretical explication. There is thus an intimate relation between the two approaches. A significant accomplishment of this research over the years is the development of an integrated and unified language for discussing the empirical aspects of meaning, information and sign structure. This in turn allows the refinement of vague and intuitive concepts in these areas into empirically testable concepts, the development of reliable, precise and valid instruments for the measurement of these concepts, and the development of experimental techniques for investigating the relations between these concepts. Thus explication and experiment have become interdependent, self-improving functions. The language is called the language of menetics (Pearson, 1977). The term originally stemmed from the “etics” of meaning. but the language has been found to be sufficiently general that it is now offered as an empirical language for much of semiotics and information science. In addition to presenting the language and describing its development, the work cited also gives examples of use of the language to discuss and analyze experimental results and to abduce theoretical results. A result of significance is an interpretation of Peirce’s system of signs in terms of an elementary prototheory of sign structure (Pearson and Slamecka, 1977a). The theory, called the Universal Sign Structure Model, argues that of the many taxonomies or classification schemes for signs, only the one proposed by Charles Peirce has proved to be satisfactory in every empirical setting or which a classification was wanted: and it shows how the applicability and usefulness of the Peircean scheme can be explained in terms of some very simple sign structure concepts. The theory is composed of a Universal Sign Structure Diagram, three principles, and nine representation theorems. The three principles are: The Representation Principle: A sign must consist of a trinary relation, and it must represent. A sign, therefore, consists of three parts: a syntactic structure, a semantic structure, and a pragmatic structure. The Principle of Internal/External Balance: The internal and the external structure of a sign must be balanced, consisting of exactly one internal component for each external component and vice versa. The internal components are called components of meaning. The external components are called information generators. The Principle of Additional Structure: Whenever a sign has more than the minimum structure, the additional structure is built up from the center out as per the Universal Sign Structure Diagram, and for each dimension independently. The application of the Universal Structure Model to understanding the foundations of information processes has been elaborated in several papers demonstrating the power of the semiotic approach for the development of empirical models of such information processes as
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those studied by researchers in psycholinguistics, information processing, communication theory, perceptual psychology and cognitive psychology. An integrated discussion and analysis is achieved and many suggestions for future work in experimental semiotics as related to communication can now be made (Pearson and Slamecka, 1977a; Slamecka and Pearson, 1978). Most of the instrumentation and experimental procedures and techniques developed in the SemLab are presented and described in the Proceedings of the 1976 Workshop on Experimental Semiotics. One of the fruitful marriages between theoretical explication and experimental development has been the invention of the eidometer to measure the deviation in the shape of artificial words from the “normal” shape of words for a given natural language. The recent results have led to suggestions for the refinement of the Miller-Bruner-Postman experiment for measuring information processing rates as a function of word shape, and for measuring Shannon’s redundancy curve for natural language (Pearson, 1978). Related research is directed toward the investigation of the quantitative relationships between the concepts of rank, frequency, word-types, and word-tokens for American English using a standard corpus of machine-readable text developed by Brown University and special software developed in the SemLab. Each of the equations proposed in the literature was tested against the entire corpus of a million words and most were found to be poor approximations of the observed results. Several equations were recommended for further testing and two new ones were suggested (Pearson, 1977a). The research employs automatic instrumentation for counting and measuring various aspects of basic sign phenomena; the instrumentation can also be applied to the observation and mathematical analysis of natural language (Flowers, 1976). Software programs have been written to count word-types and word-tokens in machine-readable natural language text, and producing rank-frequency distributions; perform the regression analysis of an observed distribution; observe and analyze linguistic and information structures; count polygrams in machine-readable text; use polygram frequency tables to produce artificial word shapes using Markov information sources of orders 0 through 3. The latter program represents the state of the art today in artificial word generation, and its latest version (producing artificial words of any finite Markov order) is a breakthrough in the state of the art of word generation. An entirely different kind of interaction between theory and experiment but regarding the concept of sign shape has led to a proposal to use the Kolmogorov potential as a measure of algorithmic information. This proposal is made in a historical and tutorial review paper that prepares the way for a semiotic explication of algorithmic information and eidontic complexity and their relation to sign shape (Pearson and Zunde, 1978). In line with the significance attributed to semiotic research, the School was active in the formation of a new scientific society, the Semiotic Society of America, and hosted the first annual conference of the Society in September 1976. The School was also active in establishing, within the SSA, a special interest group for empirical semiotics.
Human information processes and their algorithms The direction of research that has been taken by the School in the area of artificial intelligence may be divided into two main categories: the development of algorithms for “intelligent” performance, and the modeling of human information processes. These approaches are related in that the eventual goal of each is to describe or design computer programs and systems that exhibit behaviors and performances that are ordinarily associated with the human cognitive processes such as problem solving, game playing, object recognition, cognitive learning, information processing, and natural language understanding. They differ in the methodologies used to achieve this goal. Development of algorithms for intelligent performance. In designing programs for intelligent performance, the designer is primarily interested that his system succeed in performing the task that it was intended to accomplish. This performance-attainment strategy is known as the engineering approach. The processes used for achieving successful performance processes are usually related to the availability of technology and the principle of performance efficiency. Research conducted in the framework of the engineering approach during the last ten years
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at the School of Information and Computer Science may be classified into two main areas: machine vision and representation; and language understanding and speech recognition. In the area of machine vision the research emphasis has been on automatic picture analysis and object recognition (Baird, 1972; Baird and Kelly, 1974; Grosky and Wang, 1975). One research effort (Baird, 1972) led to the development of a new paradigm for picture recognition such that contextual information could be explicitly utilized leading to recognition performance that implicitly uses intensional class descriptions. More specifically, the paradigm relies on a procedure whereby the “semantics” of a picture or sensory information is provided. In addition, a set of rules of inference is developed. This set acts on a scene description resulting in the generation or “discovery” of new properties and relations. Subsequently a simplified and more limited version of the “semantic” paradigm was reported on. A new technique was introduced and described for recognizing objects in digitized gray level pictures, based on (a) the use of a preprocessing procedure for determining the existence of “primitive” properties and relations which hold for or between objects in a picture; (b) the succinct and explicit representation, in the form of “rules of inference” of the relational structure of the objects or scenes to be analyzed; and (c) the unique application of the rules to a sequence of thresholded versions of the input picture. The technique was illustrated in the recognition of facial features. The overall objective of the School’s research in machine vision has been the development of computer representation for pictorial concepts. A primary goal of this work was to develop a method for representing pictures in computers based on types of vertices and connectivity of vertices; and to describe pictorial concepts in terms of this representation method for purposes of recognition. In the area of computational language analysis, an interesting contribution has been made on the systematic decomposition and automatic recomposition of Chinese ideograms by means of computational techniques (Ting and Horng, 1975). The principal concepts associated with the techniques are: (a) a decomposition procedure used to create a pseudo-alphabet for uniquely representing most Chinese characters; (b) the existence of natural character writing sequences that may conveniently be adapted in conjunction with the proposed alphabetic set for input; and (c) the existence of a set of identifiable structured relationships among the sub-components which may be employed within the computational systems for automatic recomposition. A two-step process was employed for the recomposition procedure. The first step converts the alphabetic string into an intermediate sub-character string. In the second step, the natural structured characteristics are then analyzed to obtain the transformational vectors and control indicators, and these vectors and indicators are used in the recomposition process. Research in this area is still current. Presently, the associated rules, parameters and proposed alphabet and sub-character sets are being refined. The modeling of human information processes. The computer modeling of human information processes is essentially the casting of psychological and information processing theories, hypotheses, and models in terms of formal algorithms and computer programs. This approach is largely empirical and presupposes systematic inquiry in the area of human information processing. There are two empirical problems associated with this approach: one has to do with identifying and applying reliable techniques to collect data on information processing behaviors that may be used in developing computer models; the other is that of constructing appropriate measures for the validation of algorithmic models and hypotheses. The School’s research in this area has dealt with various aspects of these methodological problems. The focus has been on two key issues: (1) strategies for information acquisition, and (2) problem solving and strategies for representation. In the area of strategies for information acquisition, one emphasis has been on the development of semantic information measures to assess the status of information flow between the subject and an information source as defined by a well-structured set of experimental conditions (Coulter, 1974; Coulter and Siegmann, 1974; Siegmann et al., 1974). In traditional experiments requiring information acquisition (e.g. learning and concept formation), trials are presented in a fixed or random order. This procedure allows the subject little or no opportunity to control the sequence of communication events and thereby restricts the range of behaviors displayed. Such procedures limit the subject’s information acquisition
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strategies. As a result, conclusions drawn from traditional experiments may seriously underestimate the importance of subject-directed activities in acquiring information and may present a distorted picture of human information processing. Alternatively, the School’s aim has been to develop a linguistically oriented methodology for conducting experiments in which the subject may play an active role in a dialogue or conversation on a trial by trial basis. In a related project the researchers conducted a dialogue experiment using rote material which led to the development of a model for human information acquisition strategies. The model was designed to (a) account for strategy differences induced by instructional set; (b) describe individual differences in strategies; and (c) incorporate and predict previous results of human scanning processes. The model is based on semantic information measures that are employed to describe information transfer in the dialogue experiments. A computer program on these measures calculates the theoretical information state of subjects at each response state. These calculations, along with corresponding plots produced by the program, allow a quantitative analysis of different learning strategies. Another direction of research on human information acquisition investigated factors that were conjectured to affect human indexing performance. In a related work, a measure of indexing consistency based on the concept of a fuzzy set was developed. Both projects are described in Chapter III. In the area of problem solving, the main emphases have been on the question of problem formulation and problem representation (Badre and Starks, 1973; Badre, 1974; Badre and Slamecka, 1976; Kochen and Badre, 1974). The term problem formulation refers to the process of generating a specific problem statement that permits a solution to a given problem. When the initial presentation lacks the necessary and sufficient information to find a solution, then it is said that the problem statement is ill-defined or incomplete. When a problem solver is given an incomplete problem statement, he must move to reformulate the statement by specifying the missing information. This process of having to reformulate the problem statement makes it necessary for the problem solver to shift his representation of the problem. It is on the question of shifts of representation that new contributions have been made. Let representation R(t) and a given time be defined as a fourtuple L(t), H(t), B(t), F(t) such that L(t) is an internal processing language specified by terminal and non-terminal vocabulary denoting constants and variables; H(t) is a set of hypotheses, its members well-formed i = 1,. . . , n, sentences, H,, . . . Ii,, and with Hi is associated a weight wi(t) and a saliency, ai( where n equals the number of salient hypotheses; B(t) is a data base associated with a system of interpretation and consisting of a set of elements in a universe of discourse which can be compared to observed states of the external environment; F(t) is a set of operators. This property of a representation allows the transfer from one hypothesis to another. A shift of representation is said to occur if L(t,) z L(t,) or H(t,) # H(t,) or B(t,) z I or F(t,) # F(t,). Shifts in H(t) are characterized by changes in weight and saliency of hypotheses. The saliency of an hypothesis, ai( takes only the values 0 or 1. The reason is that an hypothesis is either being entertained and therefore in salient storage with value 1, or not being considered and thus in insalient storage with value 0. When an hypothesis is retrieved from insalient to salient storage then a saliency shift of representation has occurred. Hence, every time a new hypothesis is tested, it is assumed that a saliency shift has taken place. A new hypothesis is defined as the first test-occurrence of an hypothesis. The testing of an hypothesis is a function of the weight assigned those hypotheses in salient storage. If the only change that occurs before testing is a reassignment of weights, then this is called a weight shift. It is assumed here that the key processing feature of insight problem-solving is the saliency shifting representations. It can be argued that shifts in B(t) constitute saliency shifts since new hypotheses necessarily accompany change in data-base (Badre, 1974). Based on the above definition of a shift of representation, it has been confirmed (Kochen and Badre, 1974, 1976) that for a class of permutation problems the acquisition of representations is (1) a function of (a) what is contained in the statement of the problem, and (b) the experience of the problem solver; and (2) different in process between problems that are ill-defined and those that are well-defined. In addition to this confirmation, the researchers have
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proposed and tested a way to measure the quality of question-protocols as indicative of problem solving performance. The long range objective of research on problem solving at the School of Information and Computer Science is to better understand the information processes that lead to the formulation of principles for developing algorithms and computer systems that model expert problem solving of ill-defined problems. In a separate line of research, a generalized symbolic model of man-machine interactions has been described (Ting and Badre, 1975. 1976). The model was intended to represent the man-machine interactive behaviors of interactive adaptive logic systems. The use of the model was demonstrated by its application to an on-line audiographic learning facility (Slamecka, 1973) with emphasis on a pre-selected set of interactive functions. The more fundamental research effort, summarized in this section, has, at least in some instances, preceded and contributed to the design of experimental systems which are intended to aid humans in the performance of “intelligent” operations. The latter systems are described in Chapter III of this review. REFERENCES shifting on the solving of insight problems. In Information Proc. of the 37th America1 Society for Information Science Annual Meeting, Atlanta,
Badre, A. N. (1974). The effects of hypothesis Utilities:
Georgia. Badre, A. N. and Slamecka, V. (1976). Problem-solving approaches to clinical decision processing. Biosci. Commun. 2, 269-281. Badre, A. N. and Sharks, D. D. (1973). Concept learning as a function ability and method. In Proc. of the American Psychological Association, Montreal. Baird, M. L. (1972). A. Paradigm for Semantic Picture Recognition. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Baird, M. L. and Kelly, M. D. (1974). Recognizing objects by rules of inference on sequentially threshold Gray-level pictures. Research Rep. GMR-1436. Computer Science Department, General Motors Corporation Research Laboratories, Warren, Michigan. Baird, M. and Kelly, M. D. (1974). A paradigm for semantic picture recognition. Pattern Recognition 6, 61-74. Chiaraviglio, L. (1969). Performance, collateral knowledge and analytic hypothesis. L’age de /a Science I, 9-20. Chiaraviglio, L. and Gough, J., Jr. (1970). Towards a syntax-monitored semantic pattern recognition. In Progress of Cybernetics: Proc. of the Int. Congress of Cybernetics (Ed. by J. Rose), Vol. III. Gordon & Breach, London. Coulter, N. S. (1974). A Human Information Acquisition Model Based on Dialog Experimentation Which Incorporates Display Eflects. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Coulter, N. S. and Siegmann, P. J. (1974). Acquisition strategies revealed by dialog experimentation. In Information Utilities: Proc. of the 37th America1 Society for Information Science Annual Meeting, Atlanta, Georgia. Dexter, M. E. (1972). A Study of Information Control in Computer-Aided Instruction. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Plowers, J. (1976). Progress in semiotic software at Georgia Tech’s SemLab. Semiotic Scene 1. Gough, J., Jr. (1967). On the German locative-a study in symbols. Mech. Transl. 10,68-83. Gough, J., Jr. (1969). Papers on the English determiners and the base structure of the English noun phrase. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1969a). The syntax-based semantics of the English determiners “O”, “A” and “THE”. Papers in Linguistics 1, 414. Gough, J., Jr. (1970). A semiotic base for grammar. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1975). The primitive semiotic role of indexical symbolism. In Research 197C75:Annual Progress Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. (1975a). Man’s primal language. In Proc. of the 5th Int. Congress of Logic, Methodology and Philosophy of Science, London, Canada.
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Gough, J.. Jr. (1976). A primitive phenomenological semiotic paradigm for language. In Proc. of the 1976 Annual Conf. of the Semiotic Society of America, Atlanta, Georgia. Cough, J., Jr., Burrows, W. S., Roehrkasse, R. C. and Herbster, R. E. (1%8). Analysis of verb tense in scientific articles. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Gough, J., Jr. and Chiaraviglio, L. (1970). On the base referential structure of the English noun phrase. Foundations of Language 6,447-462. Gough, J., Jr. and Valach, M. (1974). Indexical symbolism: a primitive semiotic system. In Information Utilities: Proc. of the 37th Annual Meeting of the American Society of Information Science, Atlanta, Georgia. Grosky, W. and Wang, S. (1975). A language for two-dimensional digital picture processing. In Proc. of the Association for Computing Machinery Special Interest Group for Programming Languages/Special Interest Group for Computer Graphics-Hotida Int. University Symp. on Graphic Languages, Miami, Florida. Hawkey, R. L. (1%8). Some representational functions of writing systems. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Hawkey, R. L. (1%9). Towards a Descriptive Apparatus for the Synchronic Analysis of Writing Systems. Ph.D. Thesis. Vanderbilt University, Nashville, Tennessee. Hawkey, R. L. (1971). A critique of certain basic notions in Chomsky’s Syntactic Structures. Folia Linguistica 4, 193-209. Kochen, M. and Badre, A. N. (1974). On the precision of adjectives which denote fuzzy sets. J. Cybernetics 4, 49-59. Kochen, M. and Badre, A. N. (1974). Questions and shifts of representation in problem-solving. Am. J. Psychol. 81, 369-383. Kochen, M., Badre, A. N. and Badre, B. (1976). On recognizing and formulating mathematical problems. J. Instruct. Sci. 5, 115-131. Pearson, C. (1975). Lab Manual for Semiotics. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (1976a). Communication Processes. Mimeographed course notes. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (1977). Towards an Empirical Foundation of Meaning. Ph.D. Thesis. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. (Ed.) (1977a). Proc. of the 1976 Annual Conference of the Semiotic Society of America, Atlanta, Georgia. Pearson, C. (1978). Review of Information and Structure by Garner, W. P. Computing Rev. Feb. 1978. Pearson, C. (1978). An objective concept of “word shape” for natural language. (To appear in the Proc. of the 1977 Annual Conf. of the Semiotic Society of America, Denver, Colorado.) Pearson, C. and Slamecka, V. (1974). Semiotic foundations of information science. In Research 1973-74: Annual Progress Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1975). Semiotic foundations of information science. Research Rep. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1976). Semiotic foundations of information science. Research Rep. School of Information Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1977). A theory of sign structure. Bull. Semiotic Sot. Am. l(2), l-22. Pearson, C. and Slamecka, V. (1977a). Semiotic foundations of information science. Research Rep. School of Information Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Slamecka, V. (1978). Review of experimental work in semiotics. (To appear in Progress in the Communication Sciences 1.) Pearson, C., Slamecka, V., Zunde, P., Flowers, J., Betts, R., Shin, K. J. and Canyas, D. (1975). Semiotic foundations of information science. In Research 1974-75: Annual Progress Rep. School of Znformation and Computer Science, Georgia Institute of Technology, Atlanta, Georgia. Pearson, C. and Zunde, P. (1978). The Kolmogorov potential as a measure of algorithmic information. (To appear in Int. Z. Comput. Inform. Sci.) Rogers, D. E. (1964). Context-sensitivity in the verbal root set of Panini’s grammar. In Towards Tomorrow’s Linguistics (Ed. by R. W. Shuy and C. J. N. Barley). Georgetown University Press, Washington D.C. Siegmann, P. J., Coulter, N. S. and Stapleton, M. S. (1974). Methodology utilizing semantic information measures for dialogue experiments. In Information Utilities: Proc. of the 37th American Society for Information Science Annual Meeting, Atlanta, Georgia.
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Slamecka, V. (1%6). Principles of substantive analysis of information. In Proc. of the 1965 Congress of the ht. Federation for Documentation, pp. 22!IL234. Spartan Books, Washington. Slamecka, V. (1973). An audiographic system for self-instruction. J. Am. Sot. Injorm. Sci. 24, 405415. Slamecka, V. and Pearson, C. (1975). Information science. In Encyclopedia of Computer Science (Ed. by A. Ralston and C. L. Meek). Petrocelli/Charter, New York. Slamecka, V. and Pearson, C. (1978). The portent of signs and symbols. In The Many Faces of Information Science (Ed. by E. Weiss), pp. 105-126. Westview Press, Boulder, Colorado. Stapleton, M. L. (1974). A Methodology Utilizing Semantic Information Measures for Conversational or Dialogue Experiments. Ph.D. Thesis. School of Information and Computer Science. Georgia Institute of Technology, Atlanta, Georgia. Ting, T. C. and Badre, A. N. (1975). Modelingco-adaptive man-machine interactive systems. In Proc. of the 1975 Southeastern Conj. of the Society for General Systems Research, Athens, Georgia. Ting, T. C. and Badre, A. N. (1976). Dynamic model of man-machine interactions: design and application with an audiographic learning facility. J. Man-machine Studies 8, 75-88. Ting. T. C. and Horng, C. S. (1975). Graphemic analysis and synthesis of Chinese ideograms. In Proc. of the 1975 Computer Science, Washington, D.C. Ting, T. C. and Horng, C. S. (1975a). Toward a systematic decomposition and automatic recomposition of Chinese ideographs. In Proc. of the 1975 Int. Computer Symp., Taipei, Republic of China. Valach, M. (1970). A Q-graph approach to parsing. In Proc. of the Conf. on Linguistics, University of Iowa. Winner, R. I. (1973). Cartoons: an initial investigation of animated graphs. In Proc. of the 1973 Annual Nat. Conf. of the ACM, Atlanta, Georgia. Zunde, P. (Ed.) (1974). Information Utilities: Proc. of the 37th Annual Meeting of the American Society of lnjormation Science, Atlanta, Georgia. Zunde. P. and Dexter, M. E. (1%8). Statistical models of index vocabularies. In J. Am. Sot. Inform. Sci. 5, 73-78.
3.
THEORY OF COMPUTATON
The School of Information and Computer Science has pursued an active program of research in theoretical computer science since 1968. The general orientation of its research program is metatheoretical-concerned more with unifying principles than with specific problems-and the directions taken by its researchers in the theory of computing have their basis in this milieu. Given this non-standard backdrop, the main lines of research at the School have paralleled national research interests; in several instances, however, our research results pre-date trends which later appear in the general literature. The specific contributions of the School’s researchers will be discussed under the following broad categories: (1) automata, forma1 languages, algorithms, complexity; (2) applications of logic to computer science; (3) new models of computation; and (4) current trends.
Automata, formal languages,
algorithms, complexity
Considerable development of the theory of systems of automata, arrayed in geometrical fashions, has taken place at the School between 1968 and 1976. One class of problems successfully addressed is the relationship between parallel and sequential nodes of operation of cellular arrays. An especially attractive by-product of these results is the ability to prove results concerning the processing of n-dimensional patterns (n 2 2). For definitions, let us consider a genera1 tessellation mode1 consisting of a countable set of uniform finite-state machines which are interconnected in some fashion which can be specified by a local neighborhood structure. Given the state of a machine M; and its neighbors N;, . . . , Nk, a local transformation determines the next state of Mi as a function of the k + 1 “local” states. A configuration of a tessellation automaton is defined by state description of the component machines. Parallel transformations update the configurations as follows: the state machine in a successor configuration of c is a function of the k + 1 states in configuration C* which differs from c only in that the states of all cells processed before c have been updated. Tessellation automaton TA simulates automaton TAT in (t/q) real-time if configurations reachable by q transformations in TA are reachable in at most t transformations in TA2. In (Grosky