32 search results - page 6 / 7 » Kernel-Based Reinforcement Learning on Representative States |
ICML
2006
IEEE
14 years 9 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 ...
ATAL
2008
Springer
13 years 10 months ago
2008
Springer
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
ICML
2001
IEEE
14 years 9 months ago
2001
IEEE
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
TSMC
2008
13 years 8 months ago
2008
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
ICML
1996
IEEE
14 years 9 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...