Near-optimal anytime coalition structure generation

Talal Rahwan, Sarvapali D. Ramchurn, Viet Dung Dang, Nicholas R. Jennings

    Research output: Contribution to journalConference article

    Abstract

    Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithm for coalition structure generation that is faster than previous anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 66% less memory.

    Original languageEnglish (US)
    Pages (from-to)2365-2371
    Number of pages7
    JournalIJCAI International Joint Conference on Artificial Intelligence
    StatePublished - Dec 1 2007
    Event20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India
    Duration: Jan 6 2007Jan 12 2007

    Fingerprint

    Multi agent systems
    Dynamic programming
    Data storage equipment

    ASJC Scopus subject areas

    • Artificial Intelligence

    Cite this

    Rahwan, T., Ramchurn, S. D., Dang, V. D., & Jennings, N. R. (2007). Near-optimal anytime coalition structure generation. IJCAI International Joint Conference on Artificial Intelligence, 2365-2371.

    Near-optimal anytime coalition structure generation. / Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet Dung; Jennings, Nicholas R.

    In: IJCAI International Joint Conference on Artificial Intelligence, 01.12.2007, p. 2365-2371.

    Research output: Contribution to journalConference article

    Rahwan, Talal ; Ramchurn, Sarvapali D. ; Dang, Viet Dung ; Jennings, Nicholas R. / Near-optimal anytime coalition structure generation. In: IJCAI International Joint Conference on Artificial Intelligence. 2007 ; pp. 2365-2371.
    @article{0bb0a1329d9b4216b26ede100b2d5076,
    title = "Near-optimal anytime coalition structure generation",
    abstract = "Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithm for coalition structure generation that is faster than previous anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99{\%} efficient in 0.0043{\%} of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 66{\%} less memory.",
    author = "Talal Rahwan and Ramchurn, {Sarvapali D.} and Dang, {Viet Dung} and Jennings, {Nicholas R.}",
    year = "2007",
    month = "12",
    day = "1",
    language = "English (US)",
    pages = "2365--2371",
    journal = "IJCAI International Joint Conference on Artificial Intelligence",
    issn = "1045-0823",

    }

    TY - JOUR

    T1 - Near-optimal anytime coalition structure generation

    AU - Rahwan, Talal

    AU - Ramchurn, Sarvapali D.

    AU - Dang, Viet Dung

    AU - Jennings, Nicholas R.

    PY - 2007/12/1

    Y1 - 2007/12/1

    N2 - Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithm for coalition structure generation that is faster than previous anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 66% less memory.

    AB - Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithm for coalition structure generation that is faster than previous anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 66% less memory.

    UR - http://www.scopus.com/inward/record.url?scp=84880894227&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84880894227&partnerID=8YFLogxK

    M3 - Conference article

    SP - 2365

    EP - 2371

    JO - IJCAI International Joint Conference on Artificial Intelligence

    JF - IJCAI International Joint Conference on Artificial Intelligence

    SN - 1045-0823

    ER -