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IMPACTing SHOP: Putting an AI Planner Into a Multi-Agent Environment

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Abstract

In this paper we describe a formalism for integrating the SHOP HTN planning system with the IMPACT multi-agent environment. We define the A-SHOP algorithm, an agentized adaptation of the SHOP planning algorithm that takes advantage of IMPACT's capabilities for interacting with external agents, performing mixed symbolic/numeric computations, and making queries to distributed, heterogeneous information sources (such as arbitrary legacy and/or specialized data structures or external databases). We show that A-SHOP is both sound and complete if certain conditions are met.

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Authors and Affiliations

  1. The University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Jürgen Dix

  2. University of Maryland, College Park, MD, 20742, USA

    Héctor Muñoz-Avila, Dana S. Nau & Lingling Zhang

Authors
  1. Jürgen Dix
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  2. Héctor Muñoz-Avila
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  3. Dana S. Nau
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  4. Lingling Zhang
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Dix, J., Muñoz-Avila, H., Nau, D.S. et al. IMPACTing SHOP: Putting an AI Planner Into a Multi-Agent Environment. Annals of Mathematics and Artificial Intelligence 37, 381–407 (2003). https://doi.org/10.1023/A:1021560510377

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