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A performance of two learning mechanisms for small mobile robots is performed in this paper. Relational reinforcement learning, and radial basis function neural network learned by evolutionary algorithm are trained to perform the same maze exploration task and the results were compared in terms learning speed, accuracy and compactness of the resulting control mechanisms. Advantages of the chosen methods...
Intelligent embodied agents should be able to adopt to changes of the environment and to modify their behavior according to acquired knowledge. The goal of this work is the study of emergence of intelligent behavior within a simple intelligent agent. Cognitive agent functions will be realized by mechanisms based on neural networks of the perceptron type. The adaptation mechanism is realized by the...
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