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ATAL
2010
Springer
13 years 6 months ago
Learning context conditions for BDI plan selection
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
JAIR
2008
145views more  JAIR 2008»
13 years 5 months ago
Communication-Based Decomposition Mechanisms for Decentralized MDPs
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...
Claudia V. Goldman, Shlomo Zilberstein
EPIA
2005
Springer
13 years 10 months ago
Learning to Select Negotiation Strategies in Multi-agent Meeting Scheduling
In this paper, we look at the Multi-Agent Meeting Scheduling problem where distributed agents negotiate meeting times on behalf of their users. While many negotiation approaches ha...
Elisabeth Crawford, Manuela M. Veloso
ATAL
2005
Springer
13 years 10 months ago
Agent-organized networks for dynamic team formation
Many multi-agent systems consist of a complex network of autonomous yet interdependent agents. Examples of such networked multi-agent systems include supply chains and sensor netw...
Matthew E. Gaston, Marie desJardins
ML
1998
ACM
220views Machine Learning» more  ML 1998»
13 years 4 months ago
Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Toshiharu Sugawara, Victor R. Lesser