Coalitions among computationally bounded agents

Abstract

This paper analyzes coalitions among self-interested agents that need to solve combinatorial optimization problems to operate e ciently in the world. By colluding coordinating their actions by solving a joint optimization problem the agents can sometimes save costs compared to operating individually. A model of bounded r ationality is adopted where computation resources are costly. It is not worthwhile solving the problems optimally: solution quality is decision-theoretically traded o against computation cost. A normative, application-and protocol-independent theory of coalitions among boundedrational agents is devised. The optimal coalition structure and its stability are signi cantly a ected by the agents' algorithms' performance pro les and the cost of computation. This relationship is rst analyzed theoretically. Then a domain classi cation including rational and bounded-rational agents is introduced. Experimental results are presented in vehicle routing with real data from ve dispatch centers. This problem is NP-complete and the instances are so large that|with current technology|any agent's rationality is bounded by computational complexity.

Sequentially optimal repeated coalition formation under uncertainty

“…Coalition formation is the process by which individual agents form such coalitions, generally to solve a problem by coordinating their efforts. The coalition formation problem can be seen as being composed of the following activities [48]: (a) the search for an optimal coalition structure; (b) the solution of a joint problem facing members of each coalition; and (c) division of the value of the generated solution among the coalition members. While seemingly complex, coalition formation can be abstracted into a fairly simple model under the assumption of transferable utility, which assumes the existence of a (divisible) commodity (such as "money") that players can freely transfer among themselves.…”

Handling Communication Restrictions and Team Formation in Congestion Games

“…There are also many different ways to form teams, but in this paper we use a simple model that contains similar properties to many other team models [8,20,27]. In this paper, a team is defined as an aggregation of agents where each agent:…”

“…Another issue with coalitions is that, while larger coalitions may provide more benefit, they may entail substantial costs. Sandholm and Lesser show properties of coalitions when computational cost of being part of a coalition goes up as the coalition gets bigger [27]. While in the previous examples agents are trying to maximize coalition utility or system utility, in Brooks and Durfee agents are self centered, but join congregations to try to increase their own utilities [8].…”

“…Many methods exist for coordinating the actions of autonomous agents in a large multi-agent system when those agents can fully communicate with one another [7,11,21,27,33,37]. One particular solution to that problem is given within the framework of "collectives" defined as large multi-agent systems where there is a well-defined "system utility" function which rates the possible dynamic histories of the collection, and where each agent is only concerned with maximizing its own "private utility" function [37].…”

An Approximation Method for Power Indices for Voting Games

“…In this context, cooperative game theory offers a number of solution concepts such as core, kernel, and stable solution [10]. A number of multiagent systems researchers have used and extended these solutions to facilitate automated coalition formation [16,17,14,13]. A key problem, in the context of multi-agent systems, is to study the computational aspects of the solutions that game theory provides.…”