162 search results - page 5 / 33 » Off-Policy Temporal Difference Learning with Function Approx... |
AAAI
2006
13 years 11 months ago
2006
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
ICML
2003
IEEE
14 years 10 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
CIG
2006
IEEE
14 years 3 months ago
2006
IEEE
Abstract— This paper compares the use of temporal difference learning (TDL) versus co-evolutionary learning (CEL) for acquiring position evaluation functions for the game of Othe...
IWANN
1999
Springer
14 years 2 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
ICML
2006
IEEE
14 years 10 months ago
2006
IEEE
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...