Y. Luo and L. Bölöni

Analyzing and exploiting the competitiveness of scenarios for negotiating convoy formation under time constraints


Cite as:

Y. Luo and L. Bölöni. Analyzing and exploiting the competitiveness of scenarios for negotiating convoy formation under time constraints. to be published in Multiagent and Grid Systems - an International Journal, 2009. Special Issue of Advances in Agent-mediated Automated Negotiations

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Abstract:

In the convoy formation problem, two embodied agents are negotiating the synchronization of their movement for a portion of the path from their respective sources to destinations. As equilibrium strategies are not practically possible, we are interested in strategies with bounded rationality, which achieve good performance in a wide range of practical negotiation scenarios. Naturally, the performance of a strategy is dependent on the strategy of the opponent and the characteristics of the scenario. The goal of this paper is to develop a \em collaborativeness metric of the negotiation scenario which formalizes our intuition of collaborative scenarios (where the agents' interests are closely aligned) versus competitive scenarios (where the gain of the utility for one agent is paid off with a loss of utility for the other agent). We are using the Children in the Rectangular Forest (CRF) game as a canonical model of convoy formation, assume zero initial knowledge and a negotiation protocol requiring mandatory, but non-binding evaluations of the opponents offer. We also assume that the negotiation happens in physical time. We describe two negotiation strategies: the comparatively simple Internal Negotiation Deadline (IND) strategy and the computationally more expensive Uniform Concession (UC) strategy. Then, we describe how these strategies can be augmented by collaborativeness analysis: we approximate the collaborativeness metric in the first several negotiation rounds, and use the result to cut short the negotiation when the estimated collaborativeness is lower than a threshold. Through an experimental study, we show that augmenting the strategies with collaborativeness analysis significantly improves their performance for low collaborativeness scenarios, with only a minimal penalty in high collaborativeness scenarios.

BibTeX:

@article{Luo-2009-MAGS,
    author = "Y. Luo and L. B{\"o}l{\"o}ni",
    title = "Analyzing and exploiting the competitiveness of scenarios for negotiating convoy formation under time constraints",
    journal = "to be published in Multiagent and Grid Systems - an International Journal",
    note = "Special Issue of Advances in Agent-mediated Automated Negotiations",
    year = "2009",
    abstract = {
    In the convoy formation problem, two embodied agents are negotiating the
    synchronization of their movement for a portion of the path from their
    respective sources to destinations. As equilibrium strategies are not
    practically possible, we are interested in strategies with bounded
    rationality, which achieve good performance in a wide range of practical
    negotiation scenarios. Naturally, the performance of a strategy is dependent
    on the strategy of the opponent and the characteristics of the scenario. The
    goal of this paper is to develop a {\em collaborativeness metric} of the
    negotiation scenario which formalizes our intuition of collaborative
    scenarios (where the agents' interests are closely aligned) versus
    competitive scenarios (where the gain of the utility for one agent is paid
    off with a loss of utility for the other agent).
    We are using the Children in the Rectangular Forest (CRF) game as a
    canonical model of convoy formation, assume zero initial knowledge and a
    negotiation protocol requiring mandatory, but non-binding evaluations of the
    opponents offer. We also assume that the negotiation happens in physical
    time. We describe two negotiation strategies: the comparatively simple
    Internal Negotiation Deadline (IND) strategy and the computationally more
    expensive Uniform Concession (UC) strategy. Then, we describe how these
    strategies can be augmented by collaborativeness analysis: we approximate
    the collaborativeness metric in the first several negotiation rounds, and
    use the result to cut short the negotiation when the estimated
    collaborativeness is lower than a threshold. Through an experimental study,
    we show that augmenting the strategies with collaborativeness analysis
    significantly improves their performance for low collaborativeness
    scenarios, with only a minimal penalty in high collaborativeness scenarios.
    }
}

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