1310 search results - page 141 / 262 » Progressive Optimization in Action |
143
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IWANN
1999
Springer
15 years 9 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
116
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AI
2008
Springer
15 years 4 months ago
2008
Springer
Dealing with numerical information is practically important in many real-world planning domains where the executability of an action can depend on certain numerical conditions, an...
140
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ICML
2005
IEEE
16 years 5 months ago
2005
IEEE
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
144
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ICANNGA
2007
Springer
15 years 11 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
147
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ICRA
2005
IEEE
15 years 10 months ago
2005
IEEE
Abstract— In this paper, the possibility and necessity of multistep trajectory planning in Extended Kalman Filter (EKF) based SLAM is investigated. The objective of the trajector...