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Learning a world model and planning with a self-organizing, dynamic neural system | | Marc Toussaint
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11 Jun 2003 | | Subject: | Adaptation and Self-Organizing Systems | nlin.AO q-bio | | Abstract: | We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are learned with a growing self-organizing layer which is directly coupled to a perception and a motor layer. Knowledge about possible state transitions is encoded in the lateral connectivity. Motor signals modulate this lateral connectivity and a dynamic field on the layer organizes a planning process. All mechanisms are local and adaptation is based on Hebbian ideas. The model is continuous in the action, perception, and time domain. | | Source: | arXiv, nlin.AO/0306015 | | Services: | Forum | Review | PDF | Favorites | |
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