14 search results - page 2 / 3 » Near-Optimal Reinforcement Learning in Polynomial Time |
JAIR
2011
12 years 11 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
COLT
1993
Springer
13 years 8 months ago
1993
Springer
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first pre...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...