Abstract
Here we consider the issue of choice and how neural systems can be used to investigate the processes of discrimination, as well as the evolution of different kinds of choice-related behavior in animals. We develop these ideas in the context of three studies, among others. The first study is on the evolution of specialization in animals using locust feeding behavior as the leitmotif, where decision making in individuals is modeled by a 3-layer-perceptron. In this study the fitness of individuals depends on their response to signals from plants and the density of individuals using those plants [1]. The second is a study that investigates the evolution of species recognition in sympatric taxa using female mate choice in frogs as the leitmotif [2]. Here individuals are modeled by Elman nets (3-layered perceptrons with feedback) and their fitness is determined by their ability to discriminate conspecifics from heterospecifics. The third is a study of the response characteristics of a recurrent Hopfield-type neural network to input that represents olfactory stimuli. The connectivity of this net reflects the basic architectural features of the neuron in the insect antennal lobe, as typified by cockroaches or bees [3].
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© 2000 Springer-Verlag London
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Getz, W.M., Lemon, W.C. (2000). Discriminating Gourmets, Lovers, and Enophiles? Neural Nets Tell All About Locusts, Toads, and Roaches. In: Malmgren, H., Borga, M., Niklasson, L. (eds) Artificial Neural Networks in Medicine and Biology. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0513-8_5
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DOI: https://doi.org/10.1007/978-1-4471-0513-8_5
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