458 search results - page 29 / 92 » Q-Decomposition for Reinforcement Learning Agents |
ATAL
2004
Springer
14 years 1 months ago
2004
Springer
One of the main challenges in Grid computing is efficient allocation of resources (CPU-hours, network bandwidth, etc.) to the tasks submitted by users. Due to the lack of centrali...
NIPS
1993
13 years 9 months ago
1993
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...
AAAI
2006
13 years 9 months ago
2006
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
ICCBR
2009
Springer
14 years 2 months ago
2009
Springer
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...