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ATAL
2009
Springer
15 years 11 months ago
Achieving goals in decentralized POMDPs
Coordination of multiple agents under uncertainty in the decentralized POMDP model is known to be NEXP-complete, even when the agents have a joint set of goals. Nevertheless, we s...
Christopher Amato, Shlomo Zilberstein
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 11 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
15 years 9 months ago
Importing the computational neuroscience toolbox into neuro-evolution-application to basal ganglia
Neuro-evolution and computational neuroscience are two scientific domains that produce surprisingly different artificial neural networks. Inspired by the “toolbox” used by ...
Jean-Baptiste Mouret, Stéphane Doncieux, Be...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 8 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
NIPS
2003
15 years 6 months ago
Extending Q-Learning to General Adaptive Multi-Agent Systems
Recent multi-agent extensions of Q-Learning require knowledge of other agents’ payoffs and Q-functions, and assume game-theoretic play at all times by all other agents. This pap...
Gerald Tesauro