4973 search results - page 852 / 995 » Probabilistic Algorithms in Robotics |
136
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ICML
2003
IEEE
16 years 5 months ago
2003
IEEE
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
120
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KDD
2006
ACM
16 years 5 months ago
2006
ACM
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
155
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AIIA
2007
Springer
15 years 11 months ago
2007
Springer
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
156
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ATAL
2007
Springer
15 years 11 months ago
2007
Springer
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
149
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ROBOCUP
2007
Springer
15 years 10 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...