22 search results - page 2 / 5 » Model-Based Bayesian Reinforcement Learning in Large Structu... |
FLAIRS
2001
13 years 6 months ago
2001
When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by...
ATAL
2007
Springer
13 years 11 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...
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
IJRR
2008
13 years 5 months ago
2008
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...