2003/06/11 by Marc Toussaint, Toussaint, Marc
Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #Cognitive Science and Education Research #FOS: Biological sciences #FOS: Physical sciences #Neural Networks and Applications #Neural dynamics and brain function #Quantitative Biology (q-bio) #nlin.AO #q-bio
paper · pdf · doi:10.48550/arxiv.nlin/0306015
9 pages, see http://www.marc-toussaint.net/
arxiv created 2003/06/11 · openalex publication_date 2003/06/11 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.