Bounded Incremental Real-Time Dynamic Programming

A real-time multi-step planning problem is characterized by alternating decision-making and execution processes, whole online decision-making time divided in slices between each execution, and the pressing need for policy that only relates to current step. We propose a new criterion to judge the opt...

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Veröffentlicht in:Proceedings of the Frontiers in the Convergence of Bioscience and Information Technolgies : Jeju Island, Korea, October 11-13, 2007 S. 637 - 644
Hauptverfasser: Changjie Fan, Xiaoping Chen
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2007
Schlagworte:
Algorithm design and analysis
Computer science
Decision making
Dynamic programming
Heuristic algorithms
Information technology
Process planning
Real time systems
Technology planning
Uncertainty
ISBN:9780769529998, 0769529992
Online-Zugang:Volltext
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Abstract A real-time multi-step planning problem is characterized by alternating decision-making and execution processes, whole online decision-making time divided in slices between each execution, and the pressing need for policy that only relates to current step. We propose a new criterion to judge the optimality of a policy based on the upper and lower bound theory. This criterion guarantees that the agent can act earlier in a real-time decision process while an optimal policy with sufficient precision still remains. We prove that, under certain conditions, one can obtain an optimal policy with arbitrary precision using such an incremental method. We present a bounded incremental real-time dynamic programming algorithm (BIRTDP). In the experiments of two typical real-time simulation systems, BIRTDP outperforms the other state-of-the-art RTDP algorithms tested.
AbstractList A real-time multi-step planning problem is characterized by alternating decision-making and execution processes, whole online decision-making time divided in slices between each execution, and the pressing need for policy that only relates to current step. We propose a new criterion to judge the optimality of a policy based on the upper and lower bound theory. This criterion guarantees that the agent can act earlier in a real-time decision process while an optimal policy with sufficient precision still remains. We prove that, under certain conditions, one can obtain an optimal policy with arbitrary precision using such an incremental method. We present a bounded incremental real-time dynamic programming algorithm (BIRTDP). In the experiments of two typical real-time simulation systems, BIRTDP outperforms the other state-of-the-art RTDP algorithms tested.
Author Xiaoping Chen
Changjie Fan
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  surname: Xiaoping Chen
  fullname: Xiaoping Chen
  organization: Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei
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PublicationTitle Proceedings of the Frontiers in the Convergence of Bioscience and Information Technolgies : Jeju Island, Korea, October 11-13, 2007
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Snippet A real-time multi-step planning problem is characterized by alternating decision-making and execution processes, whole online decision-making time divided in...
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StartPage 637
SubjectTerms Algorithm design and analysis
Computer science
Decision making
Dynamic programming
Heuristic algorithms
Information technology
Process planning
Real time systems
Technology planning
Uncertainty
Title Bounded Incremental Real-Time Dynamic Programming
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