1630 search results - page 68 / 326 » Coordinated Reinforcement Learning |
ATAL
2009
Springer
14 years 4 months ago
2009
Springer
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
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...
IJCAI
2007
13 years 11 months ago
2007
The options framework provides a method for reinforcement learning agents to build new high-level skills. However, since options are usually learned in the same state space as the...
ICML
2003
IEEE
14 years 10 months ago
2003
IEEE
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
ATAL
2009
Springer
14 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...