Preprocessing for Point-Based Algorithms of POMDP
نویسندگان
چکیده
منابع مشابه
Accelerating Point-Based POMDP Algorithms via Greedy Strategies
Many planning tasks of autonomous robots can be modeled as partially observable Markov decision process (POMDP) problems. Point-based algorithms are well-known algorithms for solving large-scale POMDP problems. Several leading point-based algorithms eschew some flawed but very useful heuristics to find an -optimal policy. This paper aims at exploiting these avoided heuristics by a simple framew...
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Existing complexity bounds for point-based POMDP value iteration algorithms focus either on the curse of dimensionality or the curse of history. We derive a new bound that relies on both and uses the concept of discounted reachability; our conclusions may help guide future algorithm design. We also discuss recent improvements to our (point-based) heuristic search value iteration algorithm. Our ...
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Existing complexity bounds for point-based POMDP value iteration algorithms focus either on the curse of dimensionality or the curse of history. We derive a new bound that relies on both and uses the concept of discounted reachability; our conclusions may help guide future algorithm design. We also discuss recent improvements to our (point-based) heuristic search value iteration algorithm. Our ...
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The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact solutions in this framework are typically computationally intractable for all but the smallest problems. Furthermore, until recently, the efficient approximations that were available offered few theoretical guarantees r...
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ژورنال
عنوان ژورنال: Journal of Software
سال: 2008
ISSN: 1000-9825
DOI: 10.3724/sp.j.1001.2008.01309