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ESAW
2008
Springer
15 years 5 months ago
Contribution to the Control of a MAS's Global Behaviour: Reinforcement Learning Tools
Reactive multi-agent systems present global behaviours uneasily linked to their local dynamics. When it comes to controlling such a system, usual analytical tools are difficult to ...
François Klein, Christine Bourjot, Vincent ...
145
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ICML
2007
IEEE
16 years 4 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ATAL
2009
Springer
15 years 10 months ago
Solving multiagent assignment Markov decision processes
We consider the setting of multiple collaborative agents trying to complete a set of tasks as assigned by a centralized controller. We propose a scalable method called“Assignmen...
Scott Proper, Prasad Tadepalli
ECAI
2006
Springer
15 years 7 months ago
Strategic Foresighted Learning in Competitive Multi-Agent Games
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
ATAL
2004
Springer
15 years 9 months ago
A Pheromone-Based Utility Model for Collaborative Foraging
Multi-agent research often borrows from biology, where remarkable examples of collective intelligence may be found. One interesting example is ant colonies’ use of pheromones as...
Liviu Panait, Sean Luke