Literature DB >> 1887231

Animal choice behavior and the evolution of cognitive architecture.

L A Real1.   

Abstract

Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.

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Mesh:

Year:  1991        PMID: 1887231     DOI: 10.1126/science.1887231

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  27 in total

Review 1.  Decision making in recurrent neuronal circuits.

Authors:  Xiao-Jing Wang
Journal:  Neuron       Date:  2008-10-23       Impact factor: 17.173

2.  The role of beginner's luck in learning to prefer risky patches by socially foraging house sparrows.

Authors:  Tomer Ilan; Edith Katsnelson; Uzi Motro; Marcus W Feldman; Arnon Lotem
Journal:  Behav Ecol       Date:  2013-09-10       Impact factor: 2.671

3.  Evolution of social learning when high expected payoffs are associated with high risk of failure.

Authors:  Michal Arbilly; Uzi Motro; Marcus W Feldman; Arnon Lotem
Journal:  J R Soc Interface       Date:  2011-04-20       Impact factor: 4.118

4.  Evolution of learned strategy choice in a frequency-dependent game.

Authors:  Edith Katsnelson; Uzi Motro; Marcus W Feldman; Arnon Lotem
Journal:  Proc Biol Sci       Date:  2011-09-21       Impact factor: 5.349

5.  Bayesian analysis of foraging by pigeons (Columba livia).

Authors:  P R Killeen; G M Palombo; L R Gottlob; J Beam
Journal:  J Exp Psychol Anim Behav Process       Date:  1996-10

6.  Effects of recent experience on foraging decisions by bumble bees.

Authors:  Reuven Dukas; Leslie A Real
Journal:  Oecologia       Date:  1993-05       Impact factor: 3.225

7.  Coevolution of learning and data-acquisition mechanisms: a model for cognitive evolution.

Authors:  Arnon Lotem; Joseph Y Halpern
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-10-05       Impact factor: 6.237

8.  Preferences for fixed and variable food sources: variability in amount and delay.

Authors:  M Bateson; A Kacelnik
Journal:  J Exp Anal Behav       Date:  1995-05       Impact factor: 2.468

Review 9.  Behavior systems and reinforcement: an integrative approach.

Authors:  W Timberlake
Journal:  J Exp Anal Behav       Date:  1993-07       Impact factor: 2.468

10.  The adaptive nature of the human neurocognitive architecture: an alternative model.

Authors:  P La Cerra; R Bingham
Journal:  Proc Natl Acad Sci U S A       Date:  1998-09-15       Impact factor: 11.205

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