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ICML
2008
IEEE
16 years 2 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
157
Voted
ECML
2006
Springer
15 years 5 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
NIPS
2007
15 years 3 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
99
Voted
ECML
1997
Springer
15 years 5 months ago
Ibots Learn Genuine Team Solutions
\Ibots" (Integrating roBOTS) is a computer experiment in group learning. It is designed to understand how to use reinforcement learning to program automatically a team of robo...
Cristina Versino, Luca Maria Gambardella
ICMAS
1998
15 years 2 months ago
The Moving Target Function Problem in Multi-Agent Learning
We describe a framework that can be used to model and predict the behavior of MASs with learning agents. It uses a difference equation for calculating the progression of an agent&...
José M. Vidal, Edmund H. Durfee