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A Formal Approach to Embedding First-Principles Planning in BDI Agent Systems

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Scalable Uncertainty Management (SUM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11142))

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Abstract

The BDI architecture, where agents are modelled based on their beliefs, desires, and intentions, provides a practical approach to develo** intelligent agent systems. However, these systems either do not include any capability for first-principles planning (FPP), or they integrate FPP in a rigid and ad-hoc manner that does not define the semantical behaviour. In this paper, we propose a novel operational semantics for incorporating FPP as an intrinsic planning capability to achieve goals in BDI agent systems. To achieve this, we introduce a declarative goal intention to keep track of declarative goals used by FPP and develop a detailed specification of the appropriate operational behaviour when FPP is pursued, succeeded or failed, suspended, or resumed in the BDI agent systems. Furthermore, we prove that BDI agent systems and FPP are theoretically compatible for principled integration in both offline and online planning manner. The practical feasibility of this integration is demonstrated, and we show that the resulting agent framework combines the strengths of both BDI agent systems and FPP, thus substantially improving the performance of BDI agent systems when facing unforeseen situations.

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Notes

  1. 1.

    The plan and action libraries \( \varPi \) and \( \varLambda \) are omitted under the assumption that they are static entities, i.e. they remain unchanged as the agent moves between configurations.

  2. 2.

    We only explicitly mention \( \mathcal {M} \) in the agent configuration of \( A^{2}_{goal}\); for all other rules, the library does not change and is omitted.

  3. 3.

    https://fai.cs.uni-saarland.de/hoffmann/ff.html.

  4. 4.

    Due to the lack of space, interested readers are referred to [17] for the full content. We also omit the detailed discussion of the knowledge transformation between BDI and PDDL as it is implementation-dependent.

  5. 5.

    https://github.com/kevinmcareavey/ppddl.

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Acknowledgements

This work has received funding from the EU Horizon 2020 Programme through the DEVELOP project (under grant agreement No. 688127).

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Authors and Affiliations

  1. University of Bristol, Bristol, UK

    Mengwei Xu, Kim Bauters, Kevin McAreavey & Weiru Liu

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  1. Mengwei Xu
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  2. Kim Bauters
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Correspondence to Mengwei Xu .

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Editors and Affiliations

  1. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

  2. University of Milano-Bicocca, Milan, Italy

    Gabriella Pasi

  3. Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

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Xu, M., Bauters, K., McAreavey, K., Liu, W. (2018). A Formal Approach to Embedding First-Principles Planning in BDI Agent Systems. In: Ciucci, D., Pasi, G., Vantaggi, B. (eds) Scalable Uncertainty Management. SUM 2018. Lecture Notes in Computer Science(), vol 11142. Springer, Cham. https://doi.org/10.1007/978-3-030-00461-3_23

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  • DOI: https://doi.org/10.1007/978-3-030-00461-3_23

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