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How to Form a Task-Oriented Robust Team

Published: 04 May 2015 Publication History

Abstract

How to form a team for achieving a given set of tasks is an important issue in multi-agent systems. Task-oriented team formation is the problem of selecting a group of agents, where each agent is characterized by a set of capabilities; the objective is to achieve a given set of tasks, where each task is made precise by a set of capabilities necessary for managing it. Robustness (i.e., the ability to reach the goal even if some agents break down) is an expected property of a team. In this paper, the focus is laid on the Task-Oriented Robust Team Formation (TORTF) problem. A formal framework is defined and some decision and optimization problems for TORTF are pointed out. The computational complexity of TORTF is then identified. Interestingly, TORTF does not prove more computationally demanding than the task-efficient team formation problem, i.e., robustness is in some sense "for free". In order to solve these TORTF problems, two algorithms, ART (Algorithm for Robust Team) for the decision problem and AORT (Algorithm for Optimal Robust Team) for bi-objective constraint optimization problems, are presented and evaluated on a number of benchmarks.

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  1. How to Form a Task-Oriented Robust Team

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    Published In

    cover image ACM Other conferences
    AAMAS '15: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
    May 2015
    2072 pages
    ISBN:9781450334136

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    • IFAAMAS

    In-Cooperation

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    International Foundation for Autonomous Agents and Multiagent Systems

    Richland, SC

    Publication History

    Published: 04 May 2015

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    Author Tags

    1. bi-objective constraint optimization
    2. complexity analysis
    3. robustness
    4. team formation

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    AAMAS '15 Paper Acceptance Rate 108 of 670 submissions, 16%;
    Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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    • (2024)Nash Stability in Hedonic Skill GamesProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662923(706-714)Online publication date: 6-May-2024
    • (2019)Robustness against agent failure in hedonic gamesProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367032.3367085(364-370)Online publication date: 10-Aug-2019
    • (2019)Robust Peer-Monitoring on Graphs with an Application to Suicide Prevention in Social NetworksProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3332046(2168-2170)Online publication date: 8-May-2019
    • (2019)Complexity and Approximations in Robust Coalition Formation via Max-Min k-PartitioningProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3332002(2036-2038)Online publication date: 8-May-2019
    • (2019)Robustness against Agent Failure in Hedonic GamesProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331999(2027-2029)Online publication date: 8-May-2019
    • (2018)Recoverable Team FormationProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237903(1362-1370)Online publication date: 9-Jul-2018
    • (2017)Synergistic Team CompositionProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091330(1463-1465)Online publication date: 8-May-2017
    • (2016)Mission oriented robust multi-team formation and its application to robot rescue simulationProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060685(454-460)Online publication date: 9-Jul-2016

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