144 search results - page 10 / 29 » A Cautious Approach to Generalization in Reinforcement Learn... |
ML
2002
ACM
14 years 9 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
155
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GECCO
2011
Springer
14 years 1 months ago
2011
Springer
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
AAMAS
2007
Springer
14 years 10 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
ATAL
2009
Springer
15 years 4 months ago
2009
Springer
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
AAMAS
2005
Springer
14 years 10 months ago
2005
Springer
In this paper, we focus on the coordination issues in a multiagent setting. Two coordination algorithms based on reinforcement learning are presented and theoretically analyzed. O...