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143
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ICML
1994
IEEE
15 years 8 months ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
144
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IJRR
2008
15 years 4 months ago
2008
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
134
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TSMC
2008
15 years 4 months ago
2008
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
147
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AIIDE
2006
15 years 5 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
137
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COLT
1994
Springer
15 years 8 months ago
1994
Springer
Realistic domains for learning possess regularities that make it possible to generalize experience across related states. This paper explores an environment-modeling framework tha...