Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/2984
Título : A Multi-Agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation
Autor : Busquets, Dídac, Lopez de Mantaras, Ramon, Sierra, Carles, Dietterich, Thomas G.
Palabras clave : Artificial Intelligence
Machine Learning
Robotics
Multiagent Systems
Fuzzy Logic
Fecha de publicación : 2002
Editor: Springer
Citación : Topics in Artificial Intelligence, 5th Catalonian Conference on AI, CCIA 2002 Castellón, Spain, October 2002. Proceedings. Lecture Notes in Artificial Intelligence Vol. 2504, p.p.: 269-281, Springer-Verlag, 2002.
Resumen: This paper extends a navigation system implemented as a multi-agent system (MAS). The arbitration mechanism controlling the interactions between the agents was based on manually-tuned bidding functions. A difficulty with hand-tuning is that it is hard to handle situations involving complex tradeoffs. In this paper we explore the suitability of reinforcement learning for automatically tuning agents within a MAS to optimize a complex tradeoff, namely the camera use.
Descripción : La publicación original está disponible en www.springerlink.com.
URI : http://hdl.handle.net/10261/2984
ISSN: 0302-9743
Appears in Collections:(IIIA) Artículos

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