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ATAL
2009
Springer
16 years 1 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»
16 years 1 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 11 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 10 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 8 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