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Representation of Knowledge in the Field of Fundamental Chemical Investigations. Dialogue Expert System DIACHEM
Copyright © IFAC A rt ificial Inte llige nce. Le ningrad . USSR 1983
J
REPRESENTATION OF KNOWLEDGE IN THE FIELD OF FUNDAMENT AL CHEMICAL INVESTIGATIONS. DIALOGUE EXPERT SYSTEM DIACHEM A. A. Zenkin Moscow Slate University, Mosco w, USSR
Abstract. The paper develops the definite application of some artificial intelligence researches to the field of fundamental scientific investigations. ~ Ke;words. Chemical industry; models; artificial intelligence;
' ,'
. ~'
na ural sciences; modelling; man-machine systems; vectors; set theory; computer graphics.
1. The strategical aim of any fundamental scientific investigation is the construction of a theory (of a mathematical model) for quantity correlations between empirical facts, appearances, processes or objects in a given problem field of science. As a rule, a mathematical model (MM) describes an infinite set of concrete realizations for some class of appearances. Moreover, in connection with the mathematical isomorphism principle, one and the same MM can describe appearances belonging to fully different fields of science. All this makes it possible to say that MM is a) a universal instrument of scientific cognition, b) a powerful tool for the integration (concentration) of scientific information and c) a natural "elementary" unit for scientific knowledge representation in a framework of intelligence computer systems for support of scientific investigations. Therefore, the most natural form for representation of the intellectual potential of science and, at the same time, for a representation of knowledge in the field of fUndamental scientific investigations is a hierarchy system of MM's (of scientific quantity theories for a corresponding problem field of the natural sciences).
485
2. J.Slagle (1971) defined two main directions of investigations in the field of Artificial Intelligence: 1) disclosing the essence of natural (human) intelligence by modelling behaviour similar to man and 2 ) using machine intelligence for the acquirement of a new knowledge and for the solution of "intellectually difficult problems". This work is connected with the second direction which permits us to acquire the invaluable experience that is needed to understand (and then, perhaps, to formalize) the true mechanism of human intuition of this unique fuzzy algorithm for the precise decision of tuzzy problems. ). On the basis of systems analysis of the problem which is connected with a creation of an integrated manmachine system for chemical and chemical engineering scientific investigations, the dialogue expert system DIACHEM (DIAlogue system for CHEMistry) has been worked out (Zenkin, Ustinjuk, Yemeljanova and others, 1974). The main methodological basis of DIACHEM is the following general principle: any search investigation of the problem character may be formulated as a discrete optimal control problem (Zenkin,1980). It is not surprising that there is
A.A. Zenkin
486
an intimate connection between Artificial Intelligence and optimal control problem. "In all systems which are considered today in artificial intelligence theory, - D.A.Pospelov writes, (Pospelov, 1983). - there are two principles: activity and purposefulness". But if there is a purpose then there is a set of permissible strategies for the achievement of this purpose, and the activity of the system secures a possibility of a choice of the optimal strategy from the set, i.e., purposefulness and activity lead to an optimal control problem. This approach is the basis for the unique invariantness of the structure of DIACHEM with regard to different types of chemical problems. 4. Let F be any chemical property. In the general case F = F(q,p,G(u», where q is an external influence vector, p. is a vector of parameters of MM (theory) of the property F, G is a geometry of the molecular system and u is a control vector for this geometry G. In such a case we have three main types of problems (Zenkin, 1980). a) Direct problem: to calculate a value Ft(q,p,G) of the property F for given q,p,G and MM(theory) Ft of the property F. b) Reverse problem: to find such optimal p* and u* that J(p*,u*)=min IIFt(q,p,G(u» p,u
_ Fe 1/
for a given empirical value Fe of the property F and for a given form Ft of MM (theory) of the property F. c) Problem of creatlmi a new MM: to search a form of Ft or, formally, to find n t (q,p,G ) - Fie min min ~"F i Ft P i=1
II ,
for given sets { Gil, IF~J, i=1,2, ••• n. The last problem is the most interesting one from the Artificial Intelligence point of view, and is investigated by interactive computer graphics within a framework of DIACHEM.
5. DIACHEM has the following main modules. a) Subsystem CLAREF (CLAssification, REcognition and Forecasting) (Zenkin,A.A., Zenkin, A.I., 1982),which is used for an interactive investigation of cause-consequence connections between a structure and properties of molecular systems. As consistent with our main methodology principle, the classification problem is formulated as an optimal control problem. b) Subsystem for a chemist-machine interaction. Within the framework of the subsystem a chemist interacts with a problem (but not with a computer) under investigation by the chemical language of three-dimensional models of molecular systems (Zenkin, Ustinjuk, Yemeljanova and others, 1974; Zenkin, Ustynjuk, Phedoseeva, 1974). c) Data banks of physical and chemical properties and of geometries of molecular systems. d) A knowledge base which is a hierarchy network of MM's (theories) of physical and chemical properties, processes and objects. The main feature of DIACHEM is the active use of professional experience and scientific intuition of a chemist-investigator by an application of interactive computer graphics at all stages of his investigation and decision making. REFERENCES Pospelov, D.A. (1983). A "human" reasoningS in intelligence systems. In book: Cybernetic problems. Logic of reasonings and its modelling. Nauchniy Sovet po kompleksnoy probleme "Cibernetika" Akad.Nauk SSSR, Moscow. (in Russian). Slagle, J.R. (1971). Artificial Intelligence: the Heuristic Programmr~ Approach. Mcgraw-Hill book ompany, N.Y. Zenkin, A.A. (1980). A system of Artificial Intelligence for chemical investi~tions. Dep.VfNITI, N 5086 ot 2. 2.86, 15 pp. (in Russian). Zenkin, A.A., Yu.A.Ustyniuk, and N.N.Phedoseeva (1974). Standartization of representation of the molecUlar s~stems geomet~in1ormation. oklady Akad. auk SSSR, 218 (1974), no 6, 1362-1364.1!n Russian).
Dialogue Expert System DIACHEM
Zenkin, A.A., Yu.A.Ustinjuk, L.A. Y~ljanova, and Yu.I.Torgov (1914). Specialized dialofle ~stem for chemical scIen tic vestl~tions. DokladY Akad. NaUk SS ,218 (1914)t no 1, 10)-106. (rn-Russian). Zenkin, A.A., A.I.Zenkin (1982). A method for the construction of optImal classItIcatIons. Banach Center PUblIcations, v.1. 197-204. (in Russian) •
.~.
487
J
REPRESENTATION OF KNOWLEDGE IN THE FIELD OF FUNDAMENT AL CHEMICAL INVESTIGATIONS. DIALOGUE EXPERT SYSTEM DIACHEM A. A. Zenkin Moscow Slate University, Mosco w, USSR
Abstract. The paper develops the definite application of some artificial intelligence researches to the field of fundamental scientific investigations. ~ Ke;words. Chemical industry; models; artificial intelligence;
' ,'
. ~'
na ural sciences; modelling; man-machine systems; vectors; set theory; computer graphics.
1. The strategical aim of any fundamental scientific investigation is the construction of a theory (of a mathematical model) for quantity correlations between empirical facts, appearances, processes or objects in a given problem field of science. As a rule, a mathematical model (MM) describes an infinite set of concrete realizations for some class of appearances. Moreover, in connection with the mathematical isomorphism principle, one and the same MM can describe appearances belonging to fully different fields of science. All this makes it possible to say that MM is a) a universal instrument of scientific cognition, b) a powerful tool for the integration (concentration) of scientific information and c) a natural "elementary" unit for scientific knowledge representation in a framework of intelligence computer systems for support of scientific investigations. Therefore, the most natural form for representation of the intellectual potential of science and, at the same time, for a representation of knowledge in the field of fUndamental scientific investigations is a hierarchy system of MM's (of scientific quantity theories for a corresponding problem field of the natural sciences).
485
2. J.Slagle (1971) defined two main directions of investigations in the field of Artificial Intelligence: 1) disclosing the essence of natural (human) intelligence by modelling behaviour similar to man and 2 ) using machine intelligence for the acquirement of a new knowledge and for the solution of "intellectually difficult problems". This work is connected with the second direction which permits us to acquire the invaluable experience that is needed to understand (and then, perhaps, to formalize) the true mechanism of human intuition of this unique fuzzy algorithm for the precise decision of tuzzy problems. ). On the basis of systems analysis of the problem which is connected with a creation of an integrated manmachine system for chemical and chemical engineering scientific investigations, the dialogue expert system DIACHEM (DIAlogue system for CHEMistry) has been worked out (Zenkin, Ustinjuk, Yemeljanova and others, 1974). The main methodological basis of DIACHEM is the following general principle: any search investigation of the problem character may be formulated as a discrete optimal control problem (Zenkin,1980). It is not surprising that there is
A.A. Zenkin
486
an intimate connection between Artificial Intelligence and optimal control problem. "In all systems which are considered today in artificial intelligence theory, - D.A.Pospelov writes, (Pospelov, 1983). - there are two principles: activity and purposefulness". But if there is a purpose then there is a set of permissible strategies for the achievement of this purpose, and the activity of the system secures a possibility of a choice of the optimal strategy from the set, i.e., purposefulness and activity lead to an optimal control problem. This approach is the basis for the unique invariantness of the structure of DIACHEM with regard to different types of chemical problems. 4. Let F be any chemical property. In the general case F = F(q,p,G(u», where q is an external influence vector, p. is a vector of parameters of MM (theory) of the property F, G is a geometry of the molecular system and u is a control vector for this geometry G. In such a case we have three main types of problems (Zenkin, 1980). a) Direct problem: to calculate a value Ft(q,p,G) of the property F for given q,p,G and MM(theory) Ft of the property F. b) Reverse problem: to find such optimal p* and u* that J(p*,u*)=min IIFt(q,p,G(u» p,u
_ Fe 1/
for a given empirical value Fe of the property F and for a given form Ft of MM (theory) of the property F. c) Problem of creatlmi a new MM: to search a form of Ft or, formally, to find n t (q,p,G ) - Fie min min ~"F i Ft P i=1
II ,
for given sets { Gil, IF~J, i=1,2, ••• n. The last problem is the most interesting one from the Artificial Intelligence point of view, and is investigated by interactive computer graphics within a framework of DIACHEM.
5. DIACHEM has the following main modules. a) Subsystem CLAREF (CLAssification, REcognition and Forecasting) (Zenkin,A.A., Zenkin, A.I., 1982),which is used for an interactive investigation of cause-consequence connections between a structure and properties of molecular systems. As consistent with our main methodology principle, the classification problem is formulated as an optimal control problem. b) Subsystem for a chemist-machine interaction. Within the framework of the subsystem a chemist interacts with a problem (but not with a computer) under investigation by the chemical language of three-dimensional models of molecular systems (Zenkin, Ustinjuk, Yemeljanova and others, 1974; Zenkin, Ustynjuk, Phedoseeva, 1974). c) Data banks of physical and chemical properties and of geometries of molecular systems. d) A knowledge base which is a hierarchy network of MM's (theories) of physical and chemical properties, processes and objects. The main feature of DIACHEM is the active use of professional experience and scientific intuition of a chemist-investigator by an application of interactive computer graphics at all stages of his investigation and decision making. REFERENCES Pospelov, D.A. (1983). A "human" reasoningS in intelligence systems. In book: Cybernetic problems. Logic of reasonings and its modelling. Nauchniy Sovet po kompleksnoy probleme "Cibernetika" Akad.Nauk SSSR, Moscow. (in Russian). Slagle, J.R. (1971). Artificial Intelligence: the Heuristic Programmr~ Approach. Mcgraw-Hill book ompany, N.Y. Zenkin, A.A. (1980). A system of Artificial Intelligence for chemical investi~tions. Dep.VfNITI, N 5086 ot 2. 2.86, 15 pp. (in Russian). Zenkin, A.A., Yu.A.Ustyniuk, and N.N.Phedoseeva (1974). Standartization of representation of the molecUlar s~stems geomet~in1ormation. oklady Akad. auk SSSR, 218 (1974), no 6, 1362-1364.1!n Russian).
Dialogue Expert System DIACHEM
Zenkin, A.A., Yu.A.Ustinjuk, L.A. Y~ljanova, and Yu.I.Torgov (1914). Specialized dialofle ~stem for chemical scIen tic vestl~tions. DokladY Akad. NaUk SS ,218 (1914)t no 1, 10)-106. (rn-Russian). Zenkin, A.A., A.I.Zenkin (1982). A method for the construction of optImal classItIcatIons. Banach Center PUblIcations, v.1. 197-204. (in Russian) •
.~.
487