Abstract
The paper proposes the framework for an animat control system (the Animat Brain) that is based on the Petr K. Anokhin’s theory of functional systems. We propose the animat control system that consists of a set of functional systems (FSs) and enables predictive and purposeful behavior. Each FS consists of two neural networks: the actor and the predictor. The actors are intended to form chains of actions and the predictors are intended to make prognoses of future events. There are primary and secondary repertoires of behavior: the primary repertoire is formed by evolution; the secondary repertoire is formed by means of learning. This paper describes both principles of the Animat Brain operation and the particular model of predictive behavior in a cellular landmark environment.
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Red’ko, V.G. et al. (2007). Project “Animat Brain”: Designing the Animat Control System on the Basis of the Functional Systems Theory. In: Butz, M.V., Sigaud, O., Pezzulo, G., Baldassarre, G. (eds) Anticipatory Behavior in Adaptive Learning Systems. ABiALS 2006. Lecture Notes in Computer Science(), vol 4520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74262-3_6
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DOI: https://doi.org/10.1007/978-3-540-74262-3_6
Publisher Name: Springer, Berlin, Heidelberg
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