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A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning

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Abstract

This paper presents FENOCOP, a game-theoretic approach for solving non-cooperative planning problems that involve a set of self-interested agents. Each agent wants to execute its own plan in a shared environment but the plans may be rendered infeasible by the appearance of potential conflicts; agents are willing to coordinate their plans in order to avoid conflicts during a joint execution. In order to attain a conflict-free combination of plans, agents must postpone the execution of some of their actions, which negatively affects their individual utilities. FENOCOP is a two-level game approach: the General Game selects a Nash equilibrium among several combinations of plans, and the Scheduling Game generates, for a combination of plans, an executable outcome by introducing delays in the agents’ plans. For the Scheduling Game, we developed two algorithms that return a Pareto optimal and fair equilibrium from which no agent would be willing to deviate.

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Notes

  1. http://www.icaps-conference.org/index.php/Main/Competitions.

  2. Intel Core i7-3770 CPU at 3.40 GHz, 8 GB RAM.

  3. http://icaps-conference.org/index.php/Main/Competitions.

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Acknowledgements

This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R. Jaume Jordán is funded by grant APOSTD/2018/010 of Generalitat Valenciana - Fondo Social Europeo and by UPV PAID-06-18 project.

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Authors and Affiliations

  1. Institut Valencià d’Investigació en Intel·ligència Artificial (VRAIN), Universitat Politècnica de València, Camino de Vera, s/n, 46022, Valencia, Spain

    Jaume Jordán, Alejandro Torreño & Eva Onaindia

  2. EEMCS, Algorithmics, Delft University of Technology, P.O. Box 5031, 2600 GA, Delft, The Netherlands

    Mathijs de Weerdt

Authors
  1. Jaume Jordán
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  2. Alejandro Torreño
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  3. Mathijs de Weerdt
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  4. Eva Onaindia
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Correspondence to Jaume Jordán.

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Jordán, J., Torreño, A., de Weerdt, M. et al. A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning. Group Decis Negot 30, 7–41 (2021). https://doi.org/10.1007/s10726-020-09703-0

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