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The local enhancement conundrum: In search of the adaptive value of a social learning mechanism
Affiliation:1. Infection, Prevention, and Control, Alberta Health Services, Calgary, AB, Canada;2. Computational Epidemiology and Public Health Informatics Laboratory, University of Saskatchewan, Saskatoon, SK, Canada;3. Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada;4. School of Public Health, University of Saskatchewan, Saskatoon, SK, Canada
Abstract:Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer–scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed.
Keywords:Stimulus enhancement  Local enhancement  Social foraging  Producer–scrounger game  Game theory
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