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AI
2002
Springer
14 years 9 months ago
2002
Springer
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
ICML
2001
IEEE
15 years 10 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...
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IJCAI
2007
14 years 11 months ago
2007
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
GECON
2008
Springer
14 years 10 months ago
2008
Springer
The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of arti...