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Planning-Task Transformations for Soft Deadlines

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Intelligent Agents VII Agent Theories Architectures and Languages (ATAL 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1986))

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Abstract

Agents often have preference models that are more complicated than minimizing the expected execution cost. In this paper, we study how they should act in the presence of uncertainty and immediate soft deadlines. Delivery robots, for example, are agents that are often confronted with immediate soft deadlines. We introduce the additive and multiplicative planning-task transformations, that are fast representation changes that transform planning tasks with convex exponential utility functions to planning tasks that can be solved with variants of standard deterministic or probabilistic artificial intelligence planners. Advantages of our representation changes include that they are context-insensitive, fast, scale well, allow for optimal and near-optimal planning, and are grounded in utility theory. Thus, while representation changes are often used to make planning more efficient, we use them to extend the functionality of existing planners, resulting in agents with more realistic preference models.

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Author information

Authors and Affiliations

  1. College of Computing, Georgia Institute of Technology, GA 30305, Atlanta, USA

    Sven Koenig

Authors
  1. Sven Koenig
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Editor information

Editors and Affiliations

  1. Department of Communication Sciences, “Cognitive Science”, University of Siena, piazza S.Francesco 8, 53100, Siena, Italy

    Cristiano Castelfranchi

  2. Department of Computer Science, York University, 4700 Keele Street, M3J 1P3, Toronto, Ontario, Canada

    Yves Lespérance

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© 2001 Springer-Verlag Berlin Heidelberg

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Koenig, S. (2001). Planning-Task Transformations for Soft Deadlines. In: Castelfranchi, C., Lespérance, Y. (eds) Intelligent Agents VII Agent Theories Architectures and Languages. ATAL 2000. Lecture Notes in Computer Science(), vol 1986. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44631-1_21

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  • DOI: https://doi.org/10.1007/3-540-44631-1_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42422-2

  • Online ISBN: 978-3-540-44631-6

  • eBook Packages: Springer Book Archive

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