181 search results - page 18 / 37 » On Policy Learning in Restricted Policy Spaces |
AAAI
2000
13 years 9 months ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
ICRA
2010
IEEE
13 years 6 months ago
2010
IEEE
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
IJCAI
2007
13 years 9 months ago
2007
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
IJCAI
2007
13 years 9 months ago
2007
Most work on Predictive Representations of State (PSRs) has focused on learning and planning in unstructured domains (for example, those represented by flat POMDPs). This paper e...