The case for a cognitive approach to animal learning and behavior

doi:10.1016/S0376-6357(01)00150-4

Behavioural Processes

Volume 54, Issues 1–3, 3 May 2001, Pages 65-78

https://doi.org/10.1016/S0376-6357(01)00150-4 Get rights and content

Abstract

The dangers of hypothesizing about unobservable cognitive mechanisms are well known to behavior analysts. I propose, however, that carefully fashioned cognitive theories that make predictions that are inconsistent with current behavioral theories can provide useful research tools for the understanding of behavior. Furthermore, even if the results of such research may be accommodated by modifying existing behavioral theories, our understanding of behavior is often advanced by the empirical findings because it is unlikely that the research would have been conducted in the absence of such cognitive hypothesizing. Two examples of the development of emergent relations are described: The first deals with the nature of a pigeon's ‘representation’ of two stimuli both of which are associated with correct responding to a third in a many-to-one matching task (stimulus equivalence or common representations). The second has to do with transitive inference, the emergent relation between two stimuli mediated by their relation to a common stimulus in a simultaneous discrimination.

Section snippets

The case for a cognitive approach to animal learning and behavior

Two very different approaches to animal cognition have appeared during the 20th century. The first approach, characterized originally by the work of Romanes (1883), can be thought of as a biological approach because of its emphasis on the genetic basis of behavior. This approach has focused on the adaptive (survival) value of cognitive processes and posits that evolution has genetically selected animals for certain cognitive abilities. According to this view, cognitive behavior evolved

Acknowledgements

This research was supported by National Science Foundation Grant IBN 941489 and National Institute of Mental Health Grants 55118 and 59194. I thank Janice Weaver, Emily Klein, and Tricia Clement for their helpful comments on an earlier version of this manuscript.

References (60)

G.W. Farthing et al.
Short-term memory and information processing in pigeons
Learn. Motiv.
(1977)
D.R. Griffin
Animal consciousness
Neurosci. Biobehav. Rev.
(1985)
J.N. Steirn et al.
Mediational use of internal representations of food and no-food events by pigeons
Learn. Motiv.
(1991)
P.J. Urcuioli
Acquired equivalences and mediated generalization in pigeon's matching-to-sample
T.R. Zentall et al.
Delayed matching in the pigeon: effect on performance of sample-specific observing responses and differential delay behavior
Learn. Motiv.
(1978)
A. Amsel
Behaviorism, Neobehaviorism, and Cognitivism in Learning Theory
(1989)
P.E. Bryant et al.
Transitive inference and memory in young children
Nature
(1971)
M.S. Blumberg et al.
Animal mind and the argument from design
Amer. Psychol.
(1995)
E.J. Capaldi
Levels of organized behavior in rats
Catania, A.C. 1996. On the origins of behavior structure. In: Zentall, T.R., Smeets, P.M. (Eds.), Stimulus class...

N. Chapuis et al.

Short cuts in dogs in natural surroundings

Quart. J. Exp. Psych.

(1987)

T.S. Clement et al.

Effect of the S− on the S+ in a simultaneous discrimination: negative value transfer or contrast

Quart. J. Exp. Psych.

(1998)

T.S. Clement et al.

Determinants of value transfer and contrast in simultaneous discriminations

Anim. Learn. Behav.

(2000)

P.A. Couvillon et al.

A conventional conditioning analysis of ‘transitive inference’ in pigeons

J. Exp. Psych. Anim. Behav. Proc.

(1992)

H. Davis

Transitive inference in rats (Rattus norvegicus)

J. Comp. Psych.

(1992)

B.R. Dorrance et al.

Within-event learning contributes to value transfer in simultaneous instrumental discrimination learning by pigeons

Anim. Learn. Behav.

(1999)

B.R. Dorrance et al.

Value transfer in a simultaneous discrimination by pigeons: the value of the S+ is not specific to the simultaneous discrimination context

Anim. Learn. Behav.

(1998)

L.von Fersen et al.

Transitive inference formation in pigeons

J. Exp. Psych. Anim. Behav. Proc.

(1991)

D.J. Gillan

Reasoning in the chimpanzee II: transitive inference

J. Exp. Psych. Anim. Behav. Proc.

(1981)

D.S. Grant

Symmetrical and asymmetrical coding of food and no-food samples in delayed matching in pigeons

J. Exp. Psych. Anim. Behav. Proc.

(1991)

D.R. Griffin

The Question of Animal Awareness

(1976)

D.R. Griffin

Animal Thinking

(1984)

G. Hall

Learning about associatively activated stimulus representations: implications for acquired equivalence and perceptual learning

Anim. Learn. Behav.

(1996)

C.L. Hull

Principles of Behavior

(1943)

C.L. Hull

The problem of stimulus equivalence in behavior theory

Psychol. Rev.

(1939)

D.H. Kaiser et al.

Perceptual learning in pigeons: decreased ability to discriminate samples mapped onto the same comparison in many-to-one matching

Psych. Bull. Rev.

(1997)

A.C. Kamil et al.

Performance of four seed-caching corvid species in the radial-arm maze analog

J. Comp. Psych.

(1994)

S.E.G. Lea

In what sense do pigeons learn concepts?

B.O. McGonigle et al.

Are monkeys logical?

Nature

(1977)

Neiman, E.R., Zentall, T.R., 2001. Common coding of samples associated with the same comparison: the nature of the...

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The case for a cognitive approach to animal learning and behavior

Abstract

Section snippets

The case for a cognitive approach to animal learning and behavior

Acknowledgements

Learn. Motiv.

Neurosci. Biobehav. Rev.

Learn. Motiv.

Learn. Motiv.

Behaviorism, Neobehaviorism, and Cognitivism in Learning Theory

Transitive inference and memory in young children

Nature

Animal mind and the argument from design

Amer. Psychol.

Levels of organized behavior in rats

Short cuts in dogs in natural surroundings

Quart. J. Exp. Psych.

Effect of the S− on the S+ in a simultaneous discrimination: negative value transfer or contrast

Quart. J. Exp. Psych.

Determinants of value transfer and contrast in simultaneous discriminations

Anim. Learn. Behav.

A conventional conditioning analysis of ‘transitive inference’ in pigeons

J. Exp. Psych. Anim. Behav. Proc.

Transitive inference in rats (Rattus norvegicus)

J. Comp. Psych.

Within-event learning contributes to value transfer in simultaneous instrumental discrimination learning by pigeons

Anim. Learn. Behav.

Value transfer in a simultaneous discrimination by pigeons: the value of the S+ is not specific to the simultaneous discrimination context

Anim. Learn. Behav.

Transitive inference formation in pigeons

J. Exp. Psych. Anim. Behav. Proc.

Reasoning in the chimpanzee II: transitive inference

J. Exp. Psych. Anim. Behav. Proc.

Symmetrical and asymmetrical coding of food and no-food samples in delayed matching in pigeons

J. Exp. Psych. Anim. Behav. Proc.

The Question of Animal Awareness

Animal Thinking

Learning about associatively activated stimulus representations: implications for acquired equivalence and perceptual learning

Anim. Learn. Behav.

Principles of Behavior

The problem of stimulus equivalence in behavior theory

Psychol. Rev.

Perceptual learning in pigeons: decreased ability to discriminate samples mapped onto the same comparison in many-to-one matching

Psych. Bull. Rev.

Performance of four seed-caching corvid species in the radial-arm maze analog

J. Comp. Psych.

In what sense do pigeons learn concepts?

Are monkeys logical?

Nature