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ATAL
2003
Springer
14 years 3 months ago
Coordination in multiagent reinforcement learning: a Bayesian approach
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...
Georgios Chalkiadakis, Craig Boutilier
ICML
2006
IEEE
14 years 10 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto
NN
2006
Springer
13 years 9 months ago
Neural systems implicated in delayed and probabilistic reinforcement
This review considers the theoretical problems facing agents that must learn and choose on the basis of reward or reinforcement that is uncertain or delayed, in implicit or proced...
Rudolf N. Cardinal
AGENTS
1999
Springer
14 years 2 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 8 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone