1176 search results - page 126 / 236 » Sparse reward processes |
143
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IROS
2006
IEEE
15 years 10 months ago
2006
IEEE
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
146
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IAT
2005
IEEE
15 years 10 months ago
2005
IEEE
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
139
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AAAI
2008
15 years 6 months ago
2008
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
131
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ATAL
2008
Springer
15 years 6 months ago
2008
Springer
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
146
Voted
IJCAI
2003
15 years 5 months ago
2003
The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision proces...