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Automata, matching and foraging behavior of bees Export

Journal of Theoretical Biology, Vol. 175, No. 3. (07 August 1995), pp. 305-316.

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automata bees foraging matching

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Using the approach of bounded rationality and myopic learning, we attempt to explain why bees (as examples of a forager animal) do the right (optimal) thing in an environment of many foragers, namely to adopt the Ideal Free Distribution, but do the wrong thing when they are alone, namely stick to the Matching Law. We discuss two types of simple foraging strategies for bees. Each of these explicit strategies explains that in a multi-bee community the bees will distribute themselves over the nectar sources according to the Ideal Free Distribution. At the same time, these strategies explain that in single-bee experimental settings a bee will match, by its number of visits, the nectar supply from the available sources (the Matching Law). Moreover, both strategies explain that in certain situations the bees may behave as if they are risk averse. These results indicate that a competitive market in a multi-bee community permits individuals to be boundedly rational and still forage optimally.


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