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Cited by 377Insect and Arachnid Ecology and BehaviorPlant and animal studiesNeurobiology and Insect Physiology Research

The DOI matches its Crossref record; 58 of the 59 references it cites were found in a registry or an index.

Animal Choice Behavior and the Evolution of Cognitive Architecture

Real, Leslie A.·1991·Science
DOI 10.1126/science.1887231
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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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Crossref · 10.1126/science.1887231

Cites

58 of 58 references verified0 citation errors · 0 not checkable

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Citations

Cites

Flagged first, then by citations

1 of the 59 references couldn’t be matched to a known paper.

Research works printed but not linked: 14

  1. BATTALIO, R.C., AMERICAN ECONOMIC REVIEW 75: 597 (1985).
  2. BATTALIO, R.C., TESTING BETWEEN ALTERNATIVE MODELS OF CHOICE UNDER UNCERTAINTY - SOME INITIAL RESULTS, JOURNAL OF RISK AND UNCERTAINTY 3: 25 (1990).
  3. CARACO, T, QUANTITATIVE ANALYSES OF BEHAVIOR 6: 1 (1986).
  4. CARTAR, R.V., WHY ARE BUMBLE BEES RISK-SENSITIVE FORAGERS, BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY 26: 121 (1990).
  5. Heinrich, B., The Biology of Learning: 135 (1984).
  6. Menzel, R., Experimental Behavioral Ecology: 55 (1985).
  7. Newell, A., Foundations of Cognitive Science: 93 (1989).
  8. Pyke, G. H., The Ecology of Animal Movement: 7 (1983).
  9. Real, L. A., Behavioral Mechanisms in Diet Selection: 1 (1989).
  10. Rummelhart, D. E., Foundations of Cognitive Science: 133 (1989).
  11. Shettleworth, S. J., Advances in Analysis ofBehavior: 1 (1983).
  12. Simon, H. A., Foundations of Cognitive Science: 1 (1989).
  13. WILSON, B, TRANSFER OF RELATIONAL RULES IN MATCHING AND ODDITY LEARNING BY PIGEONS AND CORVIDS, QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY SECTION B-COMPARATIVE AND PHYSIOLOGICAL PSYCHOLOGY 37: 313 (1985).
  14. WUNDERLE, J.M., BEHAV ECOL SOCIOBIOL 17: 371 (1986).

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Metadata

Authors
Real, L. A.
Affiliations
University of North Carolina at Chapel Hill (US)
Corresponding author
Real, Leslie A.
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
1991-08-30
Volume
253
Issue
5023
Pages
980-986
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.1887231
OpenAlex
W1973981488
Cited by
377
References
59
Citations by year
2026: 4 · 2025: 21 · 2024: 9 · 2023: 5 · 2022: 4 · 2021: 6 · 2020: 8 · 2019: 9 · 2018: 5 · 2017: 8 · 2016: 7 · 2015: 10 · 2014: 14 · 2013: 9 · 2012: 6
FWCI
5.87
Type
journal article
Language
en
Open access
closed
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Insect Science › Insect and Arachnid Ecology and Behavior
  • Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Plant and animal studies
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
Keywords
bumblebees, foraging behavior, cognitive architecture, animal decision-making, reward allocation, heuristic rules, subjective probability, memory constraints, pattern recognition, artificial flowers
MeSH terms
Animals, Bees, Biomechanical Phenomena, Choice Behavior, Cognition, Biological Evolution, Mathematics, Models, Genetic, Probability

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