A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation

Authors:
Dídac Busquets;Ramon López de Mántaras;Carles Sierra;Thomas G. Dietterich
Affiliations:
-;-;-;-
Venue:
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Year:
2002

Citing 9
Cited 0

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Abstract

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.