Abstract
Artificial animals are hardware/software intelligent agents that must demonstrate a similar behavior like natural animals. They should have some kind of learning mechanism to acquire new information while they are interacting with their environments, so they can improve their fitness evaluation. Classifier Systems, which are a machine learning technique based on an evolutionary approach, can be applied for this purpose. In this paper we present some results of an artificial animal simulation that use two different kinds of Classifier Systems.
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