- Email: [email protected]
Taking the best for learning
Behavioural Processes 69 (2005) 147–149
Commentary
Taking the best for learning Sara J. Shettleworth Departments of Psychology and Zoology, University of Toronto, Toronto, Ont., Canada M5S 3G3
Abstract Examples of how animals learn when multiple, sometimes redundant, cues are present provide further examples not considered by Hutchinson and Gigerenzer that seem to fit the principle of taking the best. “The best” may the most valid cue in the present circumstances; evolution may also produce species-specific biases to use the most functionally relevant cues. © 2005 Elsevier B.V. All rights reserved. Keywords: Learning; Psychology; Animals
As a person with long standing interests in the evolutionary psychology of animal learning and decision making, I have always found the ABC approach congenial and welcome Hutchinson and Gigerenzer’s (2005; H&G’s) explorations of how it might be better integrated with research on animal behavior. The most solid support for ideas in much of human evolutionary psychology—for example, explanations for the design of sexual signals or mating systems—necessarily comes from comparative studies with nonhuman animals, so it is interesting to consider what new can be learned by turning the tables. In such a wide-ranging and stimulating article, there is much to discuss. I will confine myself to two points having to do with further facets of multiple cue use that H&G do not mention but might wish to consider. Studies of how and why multiple cues are used are relatively new in the context of behavioral ecology, as H&G mention. It should not be forgotten, however, E-mail address: [email protected]. 0376-6357/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.beproc.2005.02.016
that classical ethologists did recognize that multiple cues or features of sign stimuli could contribute to controlling single behavior pattern, a phenomenon known as heterogeneous summation and elegantly analyzed by Baerends and Kruijt (1973) and by Heiligenberg (1974), among others. The analysis of what happens when multiple cues are available for learning is well established in psychology, in associative learning theory. A widely applicable principle is that multiple redundant cues to the same outcome compete for the animal’s learning, with the best predictor winning (Rescorla and Wagner, 1972). If one cue is a more valid predictor than others in the situation, most learning will accrue to the most valid cue. This sounds a lot like “Take the Best” applied to the decision, which cue to learn. Moreover, just as in the examples mentioned by H&G, multiple redundant cues may not all be used. In the phenomenon of blocking, an already-learned cue to a given outcome reduces (blocks) learning of a second, redundant, predictor that is added to it (Kamin, 1969). One might think of the animal’s first encounter with the com-
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S.J. Shettleworth / Behavioural Processes 69 (2005) 147–149
bined cues as presenting it with a known predictor and an unknown, but not yet predictive cue. Unless things change, the animal, as it were, decides to continue using the best predictor in terms of its current knowledge. These principles apply widely not only to animal conditioning but also to human associative learning and contingency judgement (Siegel and Allan, 1996; Allan, 1993). Prior probabilities, perhaps established through evolution, may interact with experience to complicate this simple picture. For instance, when two cues always occurring together predict a given outcome, less is generally learned about either than when it is the sole predictor: learning is shared between the cues. However, some situations favor one cue taking the lion’s share. This can happen when one is simply louder, brighter, bigger, or in general more salient than the other. In effect, the learning system says “this will be the better one to use.” Sometimes the better cue seems obvious on functional grounds rather than simply grounds of perceptual salience. The best-known example is flavoraversion learning, where rats and other mammals learn selectively to avoid the flavor of a food that made than ill, and ignore visual or auditory cues surrounding the experience of ingesting it (Garcia and Koelling, 1966). That is, certain kinds of cues are pre selected as “the best” for certain tasks. But just as in the natural signaling systems discussed by H&G, more needs to be done to test informal notions about functional relevance of cues. In spatial behavior, multiple redundant cues do not always compete for learning; rather, different kinds of spatial cues may all be learned in parallel. For instance, learning about a localized cue that indicates the location of food or a safe refuge does not compete with learning the location of the goal with respect to the shape of local space (Pearce et al., 2001; Wall et al., 2004). Learning to use a visual cue to locate a home base does not compete with using path integration (the animal’s internal sense of direction) to locate the home (Shettleworth and Sutton, 2005). These findings are consistent with the idea that orienting by the macroscopic shape of local space and by path integration are the work of fundamental cognitive modules (Cheng, 1986; Gallistel and Cramer, 1996) in operation from the first journey into new territory, before the animal has had time to learn about local landmarks and beacons. Obviously, such cues should not prevent gradual learning about such
local environmental cues, which may in the end support more precise orientation, but by the same token they should continue to be available to fall back on if the local features change in some way. Indeed, having acquired both visual and path integration-based information, rodents will use the visual information first but then fall back on path integration if visual cues are removed or relocated (e.g., Maaswinkel and Whishaw, 1999). Spatial learning also provides several excellent examples of successive, hierarchical, use of cues that are simultaneously present. For example, black-capped chickadees (Poecile atricapilla) that have found food in a single location and then return to search for it in a test with altered cues and no reward present, look first in the global location where food had been, then in the correct location relative to an array of local landmarks (feeders), and finally in a feeder that has the same color and pattern as the original feeder (Brodbeck, 1994). In contrast, dark-eyed juncos (Junco hyemalis), do not weight spatial cues more heavily than local color and pattern in the same task. Unlike the chickadees, juncos do not hoard food and therefore might not be expected to share the emphasis on memory for spatial cues. And indeed, comparable differences in the weights given to spatial versus local visual cues are found in comparisons of food-storing birds with their nonstoring close relatives (Clayton and Krebs, 1994a,b). In summary, H&G discuss some stimulating examples of multiple cue use from behavioral ecology in terms of the ABC framework, but if they spread their net to include findings from the psychology of animal learning even more integration may be possible.
References Allan, L.G., 1993. Human contingency judgements: rule based or associative? Psychol. Bull. 114, 435–448. Baerends, G.P., Kruijt, J.P., 1973. In: Hinde, R.A., Sevenson-Hinde, J. (Eds.), Stimulus Selection. Constraints on Learning. Academic Press, London, pp. 23–50. Brodbeck, D.R., 1994. Memory for spatial and local cues: a comparison of a storing and a nonstoring species. Anim. Learn. Behav. 22, 119–133. Cheng, K., 1986. A purely geometric module in the rat’s spatial representation. Cognition 23, 149–178. Clayton, N.S., Krebs, J.R., 1994a. Memory for spatial and objectspecific cues in food-storing and non-storing birds. J. Comp. Physiol. A 174, 371–379.
S.J. Shettleworth / Behavioural Processes 69 (2005) 147–149 Clayton, N.S., Krebs, J.R., 1994b. One-trial associative memory: comparison of food-storing and non-storing species of birds. Anim. Learn. Behav. 22, 366–372. Gallistel, C.R., Cramer, A.E., 1996. Computations on metric maps in mammals: getting oriented and choosing a multi-destination route. J. Exp. Biol. 199, 211–217. Garcia, J., Koelling, R.A., 1966. Relation of cue to consequence in avoidance learning. Psychon. Sci. 4, 123–124. Heiligenberg, W., 1974. Processes governing behavioral states of readiness. Adv. Study Behav. 5, 173–200. Hutchinson, J.M.C., Gigerenzer, G., 2005. Simple heuristics and rules of thumb; where psychologists and behavioural biologists might meet. Behav. Proc. 69, 97–124. Kamin, L.J., 1969. In: Campbell, B.A., Church, R.M. (Eds.), Predictability, Surprise, Attention, and Conditioning. Punishment and Aversive Behavior. Appleton-Century-Crofts, New York, pp. 279–296. Maaswinkel, H., Whishaw, I.Q., 1999. Homing with locale, taxon, and dead reckoning strategies by foraging rats: sensory hi-
149
erarchy in spatial navigation. Behav. Brain Res. 99, 143– 152. Pearce, J.M., Ward-Robinson, J., et al., 2001. Influence of a beacon on spatial learning based on the shape of the test environment. J. Exp. Psychol.: Anim. Behav. Process. 27, 329– 344. Rescorla, R.A., Wagner, A.R., 1972. A theory of Pavlovian conditioning: variations in the effectiveness of reinforcement and nonreinforcement. In: Black, A.H., Prokasy, W.F. (Eds.), Classical Conditioning II: Current Theory and Research. AppletonCentury-Crofts, New York, pp. 64–99. Shettleworth, S.J., Sutton, J.E., 2005. Multiple systems for spatial learning: dead reckoning and beacon homing in rats. J. Exp. Psychol.: Anim. Behav. Process. 31. Siegel, S., Allan, L.G., 1996. The widespread influence of the Rescorla–Wagner model. Psychon. Bull. Rev. 3, 314–321. Wall, P., Botly, L.C.P., et al., 2004. The geometric module in the rat: independence of shape and feature learning in a food-finding task. Learn. Behav. 32, 289–298.
Commentary
Taking the best for learning Sara J. Shettleworth Departments of Psychology and Zoology, University of Toronto, Toronto, Ont., Canada M5S 3G3
Abstract Examples of how animals learn when multiple, sometimes redundant, cues are present provide further examples not considered by Hutchinson and Gigerenzer that seem to fit the principle of taking the best. “The best” may the most valid cue in the present circumstances; evolution may also produce species-specific biases to use the most functionally relevant cues. © 2005 Elsevier B.V. All rights reserved. Keywords: Learning; Psychology; Animals
As a person with long standing interests in the evolutionary psychology of animal learning and decision making, I have always found the ABC approach congenial and welcome Hutchinson and Gigerenzer’s (2005; H&G’s) explorations of how it might be better integrated with research on animal behavior. The most solid support for ideas in much of human evolutionary psychology—for example, explanations for the design of sexual signals or mating systems—necessarily comes from comparative studies with nonhuman animals, so it is interesting to consider what new can be learned by turning the tables. In such a wide-ranging and stimulating article, there is much to discuss. I will confine myself to two points having to do with further facets of multiple cue use that H&G do not mention but might wish to consider. Studies of how and why multiple cues are used are relatively new in the context of behavioral ecology, as H&G mention. It should not be forgotten, however, E-mail address: [email protected]. 0376-6357/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.beproc.2005.02.016
that classical ethologists did recognize that multiple cues or features of sign stimuli could contribute to controlling single behavior pattern, a phenomenon known as heterogeneous summation and elegantly analyzed by Baerends and Kruijt (1973) and by Heiligenberg (1974), among others. The analysis of what happens when multiple cues are available for learning is well established in psychology, in associative learning theory. A widely applicable principle is that multiple redundant cues to the same outcome compete for the animal’s learning, with the best predictor winning (Rescorla and Wagner, 1972). If one cue is a more valid predictor than others in the situation, most learning will accrue to the most valid cue. This sounds a lot like “Take the Best” applied to the decision, which cue to learn. Moreover, just as in the examples mentioned by H&G, multiple redundant cues may not all be used. In the phenomenon of blocking, an already-learned cue to a given outcome reduces (blocks) learning of a second, redundant, predictor that is added to it (Kamin, 1969). One might think of the animal’s first encounter with the com-
148
S.J. Shettleworth / Behavioural Processes 69 (2005) 147–149
bined cues as presenting it with a known predictor and an unknown, but not yet predictive cue. Unless things change, the animal, as it were, decides to continue using the best predictor in terms of its current knowledge. These principles apply widely not only to animal conditioning but also to human associative learning and contingency judgement (Siegel and Allan, 1996; Allan, 1993). Prior probabilities, perhaps established through evolution, may interact with experience to complicate this simple picture. For instance, when two cues always occurring together predict a given outcome, less is generally learned about either than when it is the sole predictor: learning is shared between the cues. However, some situations favor one cue taking the lion’s share. This can happen when one is simply louder, brighter, bigger, or in general more salient than the other. In effect, the learning system says “this will be the better one to use.” Sometimes the better cue seems obvious on functional grounds rather than simply grounds of perceptual salience. The best-known example is flavoraversion learning, where rats and other mammals learn selectively to avoid the flavor of a food that made than ill, and ignore visual or auditory cues surrounding the experience of ingesting it (Garcia and Koelling, 1966). That is, certain kinds of cues are pre selected as “the best” for certain tasks. But just as in the natural signaling systems discussed by H&G, more needs to be done to test informal notions about functional relevance of cues. In spatial behavior, multiple redundant cues do not always compete for learning; rather, different kinds of spatial cues may all be learned in parallel. For instance, learning about a localized cue that indicates the location of food or a safe refuge does not compete with learning the location of the goal with respect to the shape of local space (Pearce et al., 2001; Wall et al., 2004). Learning to use a visual cue to locate a home base does not compete with using path integration (the animal’s internal sense of direction) to locate the home (Shettleworth and Sutton, 2005). These findings are consistent with the idea that orienting by the macroscopic shape of local space and by path integration are the work of fundamental cognitive modules (Cheng, 1986; Gallistel and Cramer, 1996) in operation from the first journey into new territory, before the animal has had time to learn about local landmarks and beacons. Obviously, such cues should not prevent gradual learning about such
local environmental cues, which may in the end support more precise orientation, but by the same token they should continue to be available to fall back on if the local features change in some way. Indeed, having acquired both visual and path integration-based information, rodents will use the visual information first but then fall back on path integration if visual cues are removed or relocated (e.g., Maaswinkel and Whishaw, 1999). Spatial learning also provides several excellent examples of successive, hierarchical, use of cues that are simultaneously present. For example, black-capped chickadees (Poecile atricapilla) that have found food in a single location and then return to search for it in a test with altered cues and no reward present, look first in the global location where food had been, then in the correct location relative to an array of local landmarks (feeders), and finally in a feeder that has the same color and pattern as the original feeder (Brodbeck, 1994). In contrast, dark-eyed juncos (Junco hyemalis), do not weight spatial cues more heavily than local color and pattern in the same task. Unlike the chickadees, juncos do not hoard food and therefore might not be expected to share the emphasis on memory for spatial cues. And indeed, comparable differences in the weights given to spatial versus local visual cues are found in comparisons of food-storing birds with their nonstoring close relatives (Clayton and Krebs, 1994a,b). In summary, H&G discuss some stimulating examples of multiple cue use from behavioral ecology in terms of the ABC framework, but if they spread their net to include findings from the psychology of animal learning even more integration may be possible.
References Allan, L.G., 1993. Human contingency judgements: rule based or associative? Psychol. Bull. 114, 435–448. Baerends, G.P., Kruijt, J.P., 1973. In: Hinde, R.A., Sevenson-Hinde, J. (Eds.), Stimulus Selection. Constraints on Learning. Academic Press, London, pp. 23–50. Brodbeck, D.R., 1994. Memory for spatial and local cues: a comparison of a storing and a nonstoring species. Anim. Learn. Behav. 22, 119–133. Cheng, K., 1986. A purely geometric module in the rat’s spatial representation. Cognition 23, 149–178. Clayton, N.S., Krebs, J.R., 1994a. Memory for spatial and objectspecific cues in food-storing and non-storing birds. J. Comp. Physiol. A 174, 371–379.
S.J. Shettleworth / Behavioural Processes 69 (2005) 147–149 Clayton, N.S., Krebs, J.R., 1994b. One-trial associative memory: comparison of food-storing and non-storing species of birds. Anim. Learn. Behav. 22, 366–372. Gallistel, C.R., Cramer, A.E., 1996. Computations on metric maps in mammals: getting oriented and choosing a multi-destination route. J. Exp. Biol. 199, 211–217. Garcia, J., Koelling, R.A., 1966. Relation of cue to consequence in avoidance learning. Psychon. Sci. 4, 123–124. Heiligenberg, W., 1974. Processes governing behavioral states of readiness. Adv. Study Behav. 5, 173–200. Hutchinson, J.M.C., Gigerenzer, G., 2005. Simple heuristics and rules of thumb; where psychologists and behavioural biologists might meet. Behav. Proc. 69, 97–124. Kamin, L.J., 1969. In: Campbell, B.A., Church, R.M. (Eds.), Predictability, Surprise, Attention, and Conditioning. Punishment and Aversive Behavior. Appleton-Century-Crofts, New York, pp. 279–296. Maaswinkel, H., Whishaw, I.Q., 1999. Homing with locale, taxon, and dead reckoning strategies by foraging rats: sensory hi-
149
erarchy in spatial navigation. Behav. Brain Res. 99, 143– 152. Pearce, J.M., Ward-Robinson, J., et al., 2001. Influence of a beacon on spatial learning based on the shape of the test environment. J. Exp. Psychol.: Anim. Behav. Process. 27, 329– 344. Rescorla, R.A., Wagner, A.R., 1972. A theory of Pavlovian conditioning: variations in the effectiveness of reinforcement and nonreinforcement. In: Black, A.H., Prokasy, W.F. (Eds.), Classical Conditioning II: Current Theory and Research. AppletonCentury-Crofts, New York, pp. 64–99. Shettleworth, S.J., Sutton, J.E., 2005. Multiple systems for spatial learning: dead reckoning and beacon homing in rats. J. Exp. Psychol.: Anim. Behav. Process. 31. Siegel, S., Allan, L.G., 1996. The widespread influence of the Rescorla–Wagner model. Psychon. Bull. Rev. 3, 314–321. Wall, P., Botly, L.C.P., et al., 2004. The geometric module in the rat: independence of shape and feature learning in a food-finding task. Learn. Behav. 32, 289–298.