181 search results - page 21 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
ISDA
2009
IEEE
14 years 2 months ago
2009
IEEE
This paper presents postponed updates, a new strategy for TD methods that can improve sample efficiency without incurring the computational and space requirements of model-based ...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
IDEAL
2007
Springer
14 years 1 months ago
2007
Springer
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
APN
2003
Springer
14 years 22 days ago
2003
Springer
Model checking by exhaustive state space enumeration is one of the most developed analysis methods for distributed event systems. Its main problem—the size of the state spaces—...
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...