Article

Automated Conversion and Simplification of Plan Representations

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AAMAS '04: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3

Pages 1272 - 1273

Published: 19 July 2004 Publication History

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Abstract

As planning agents grow more sophisticated, plan representation issues arise. Planners work over increasingly large and difficult problems and output is often complex or unwieldy. Further, where planners must interact with human users - either for plan verification and analysis, or in mixed-initiative settings - plans must be represented so that the intended course of action is readily available. We propose automated techniques for simplification of, and conversion between, plan representations.

References

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{1} J. Bresina, R. Dearden, N. Meuleau, S. Ramakrishnan, D. Smith, and R. Washington. Planning under continuous time and resource uncertainty: A challenge for AI. In Proc. 18th Conf. on Uncertainty in AI, Edmonton, Alberta, 2002.

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{2} Mark Burstein and Drew McDermott. Issues in the development of human-computer mixed-initiative planning. In B. Gorayska and J. L. Mey, editors, Cognitive Technology, pages 285-303. Elsevier, 1996.

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{3} Zhengzhu Feng and Eric A. Hansen. Symbolic heuristic search for factored Markov decision processes. In Proc. 18th Natl. Conf. on Artificial Intelligence, pages 455-460, 2002.

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{4} Martin Sauerhoff and Ingo Wegener. On the complexity of minimizing the OBDD size for incompletely specified functions. IEEE Trans. CAD, 15(11):1435-1437, Nov. 1996.

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Index Terms

Automated Conversion and Simplification of Plan Representations
1. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
    1. Machine learning approaches
      1. Rule learning

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Published In

AAMAS '04: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3

July 2004

487 pages

ISBN:1581138644

Publisher

IEEE Computer Society

United States

Publication History

Published: 19 July 2004

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AAMAS04

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SIGAI

AAMAS04: The Third International Joint Conference on Autonomous Agents and Multi-Agent Systems 2004

July 19 - 23, 2004

New York, New York

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Recommendations

Continuing plan quality optimisation

Algorithms and limits for compact plan representations

Plan stability: replanning versus plan repair

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Abstract

References

Index Terms

Recommendations

Continuing plan quality optimisation

Algorithms and limits for compact plan representations

Plan stability: replanning versus plan repair

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Information

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Publication History

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