Carving the cognitive niche: optimal learning strategies in homogeneous and heterogeneous environments.

A model learning system is constructed, in which an organism samples behaviors from a behavioral repertoire in response to a stimulus and selects the behavior with the highest payoff. The stimulus and most rewarding behavior may be kept in the organism's long-term memory and reused if the stimulus is encountered again. The value of the memory depends on the reliability of the stimulus, that is, how the corresponding payoffs of behaviors change over time. We describe how the inclusion of memory can increase the optimal sampling size in environments with some stimulus reliability. In addition to using memory to guide behavior, our organism may use information in its memory to choose the stimulus to which it reacts. This choice is influenced by both the organism's memory state and how many stimuli the organism can observe (its sensory capability). The number of sampled behaviors, memory length, and sensory capability are the variables that define the learning strategy. When all stimuli have the same reliability, there appears to be only a single optimal learning strategy. However, when there is heterogeneity in stimulus reliability, multiple locally optimal strategies may exist.

[1]  M. Feldman,et al.  Individual Versus Social Learning: Evolutionary Analysis in a Fluctuating Environment , 1996 .

[2]  John Maynard Smith,et al.  Learning — an evolutionary approach , 1983, Trends in Neurosciences.

[3]  D. Cohen,et al.  The equilibrium distribution of optimal search and sampling effort of foraging animals in patchy environments , 1993 .

[4]  R. Lewontin,et al.  Organism and environment , 1997 .

[5]  S. J. Arnold The Evolution of a Special Class of Modifiable Behaviors in Relation to Environmental Pattern , 1978, The American Naturalist.

[6]  Jonathan Roughgarden,et al.  The effect of memory length on individual fitness in a lizard , 1996 .

[7]  M. Mangel Dynamic information in uncertain and changing worlds. , 1990, Journal of theoretical biology.

[8]  Marc Mangel,et al.  Motivation, Learning, and Motivated Learning , 1993 .

[9]  R. Dukas,et al.  Cognitive ecology : the evolutionary ecology of information processing and decision making , 1998 .

[10]  A. C. Lewis,et al.  Insect Learning: Ecology and Evolutinary Perspectives , 1993 .

[11]  D. Bendall,et al.  Evolution from molecules to men , 1984 .

[12]  A. Lw,et al.  A Quantitative Model of the Simpson – Baldwin Effect , 1998 .

[13]  E. Kandel,et al.  Memory suppressor genes: inhibitory constraints on the storage of long-term memory. , 1998, Science.

[14]  C. Clark,et al.  Dynamic Modeling in Behavioral Ecology , 2019 .

[15]  C. Clark,et al.  Adaptation in Stochastic Environments , 1993 .

[16]  A. C. Lewis Flower visit consistency in Pieris rapae, the cabbage butterfly , 1989 .

[17]  Marcus W. Feldman,et al.  On the Evolution of Learning: Representation of a Stochastic Environment , 1995 .

[18]  Marcus W. Feldman,et al.  Niche Construction , 2003 .

[19]  Alasdair I. Houston,et al.  Models of Adaptive Behaviour: An Approach Based on State , 1999 .

[20]  F. J. Odling-Smee,et al.  The evolutionary consequences of niche construction: a theoretical investigation using two‐locus theory , 1996 .

[21]  D. Stephens Change, regularity, and value in the evolution of animal learning , 1991 .

[22]  A. C. Lewis Memory Constraints and Flower Choice in Pieris rapae , 1986, Science.

[23]  A I Houston,et al.  Memory and the efficient use of information. , 1987, Journal of theoretical biology.

[24]  Frederick Mosteller,et al.  Stochastic Models for Learning , 1956 .

[25]  T. Johnston Selective costs and benefits of in the evolution of learning , 1996 .

[26]  F. J. Odling-Smee,et al.  Evolutionary consequences of niche construction and their implications for ecology. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[27]  T. Kotiah Sums of powers of integers—A review , 1993 .

[28]  P. Godfrey‐Smith Complexity and the function of mind in nature , 1996 .

[29]  C. L. Brewer Introduction to Psychology, Vols. 1 & 2. , 1991 .

[30]  H. Crichton-Miller Adaptation , 1926 .

[31]  David W. Stephens,et al.  On economically tracking a variable environment , 1987 .

[32]  P. Taylor,et al.  Test of optimal sampling by foraging great tits , 1978 .

[33]  H. C. Plotkin,et al.  Learning, Change, and Evolution: An Enquiry into the Teleonomy of Learning , 1979 .