creators_name: Paquier, Williams creators_name: Do Huu, Nicolas creators_name: Chatila, Raja editors_name: Prince, Christopher G. editors_name: Berthouze, Luc editors_name: Kozima, Hideki editors_name: Bullock, Daniel editors_name: Stojanov, Georgi editors_name: Balkenius, Christian type: confposter datestamp: 2004-02-12 lastmod: 2011-03-11 08:55:26 metadata_visibility: show title: A Unified Model For Developmental Robotics ispublished: pub subjects: comp-sci-neural-nets subjects: comp-sci-art-intel subjects: comp-sci-robot full_text_status: public keywords: developmental robotics, NeuSter, pulsed neural network, symbol grounding, action chaining abstract: We present the architecture and distributed algorithms of an implemented system called NeuSter, that unifies learning, perception and action for autonomous robot control. NeuSter comprises several sub-systems that provide online learning for networks of million neurons on machine clusters. It extracts information from sensors, builds its own representations of the environment in order to learn non-predefined goals. date: 2003 date_type: published volume: 101 publisher: Lund University Cognitive Studies pagerange: 173-174 refereed: TRUE citation: Paquier, Williams and Do Huu, Nicolas and Chatila, Raja (2003) A Unified Model For Developmental Robotics. [Conference Poster] document_url: http://cogprints.org/3351/1/Paquier.pdf