Abstract

The optimal coalition structure determination problem is in general computationally hard. In this article, we identify some problem instances for which the space of possible coalition structures has a certain form and constructively prove that the problem is polynomial time solvable. Specifically, we consider games with an ordering over the players and introduce a distance metric for measuring the distance between any two structures. In terms of this metric, we define the property of monotonicity, meaning that coalition structures closer to the optimal, as measured by the metric, have higher value than those further away. Similarly, quasi-monotonicity means that part of the space of coalition structures is monotonic, while part of it is non-monotonic. (Quasi)-monotonicity is a property that can be satisfied by coalition games in characteristic function form and also those in partition function form. For a setting with a monotonic value function and a known player ordering, we prove that the optimal coalition structure determination problem is polynomial time solvable and devise such an algorithm using a greedy approach. We extend this algorithm to quasi-monotonic value functions and demonstrate how its time complexity improves from exponential to polynomial as the degree of monotonicity of the value function increases. We go further and consider a setting in which the value function is monotonic and an ordering over the players is known to exist but ordering itself is unknown. For this setting too, we prove that the coalition structure determination problem is polynomial time solvable and devise such an algorithm.

Highlights

  • One of the fundamental problems in multiagent systems and in game theory is that of determining an optimal coalition structure, i.e., a partition of a set of n agents into disjoint coalitions B Shaheen FatimaAutonomous Agents and Multi-Agent Systems (2019) 33:35–83 so as to optimize the value of the partition

  • Our research advances the state of art in that we introduce a distance metric and the property of monotonicity which can be satisfied by three different types of search spaces: characteristic function games (CFGs), partition function games (PFGs), and non-separable value functions

  • With a slight abuse of notation, we assume that a value function for coalitions takes the form vC : 2N → R. This definition of value function corresponds to coalition games in characteristic function form [7], for which the optimal sequence problem is nothing but the wellknown complete set partitioning problem [20]

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Summary

B Shaheen Fatima

Autonomous Agents and Multi-Agent Systems (2019) 33:35–83 so as to optimize the value of the partition. The aim of our research is to find an effective way of expressing such regularities, in order to facilitate the development of computationally feasible methods for computing an optimal coalition structure To this end, we consider games with a player ordering and introduce a distance metric for measuring how close any two partitions are. We consider games with a player ordering and introduce a distance metric for measuring how close any two partitions are In terms of this metric, we define a property of value functions that we refer to as monotonicity. Our research advances the state of art in that we introduce a distance metric and the property of monotonicity which can be satisfied by three different types of search spaces: CFGs, PFGs (with positive only, negative only, and mixed externalities), and non-separable value functions.

The model
A distance metric
Monotonicity
Externalities and distance
An illustration for three-player games
Applications
Pros and cons of the distance metric
Related work
10 Conclusions
Full Text
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