Abstract
Resource reallocation problems are common in real life and therefore gain an increasing interest in Computer Science and Economics. Such problems consider agents living in a society and negotiating their resources with each other in order to improve the welfare of the population. In many studies however, the unrealistic context considered, where agents have a flawless knowledge and unlimited interaction abilities, impedes the application of these techniques in real life problematics. In this paper, we study how agents should behave in order to maximize the welfare of the society. We propose a multi-agent method based on autonomous agents endowed with a local knowledge and local interactions. Our approach features a more realistic environment based on social networks, inside which we provide the behavior for the agents and the negotiation settings required for them to lead the negotiation processes towards socially optimal allocations. We prove that bilateral transactions of restricted cardinality are sufficient in practice to converge towards an optimal solution for different social objectives. An experimental study supports our claims and highlights the impact of a realistic environment on the efficiency of the techniques utilized.
Highlights
In the past few years, an increasing number of studies focused on resource allocation problems, either from a centralized or a distributed point of view
Considering that neither omniscient agents nor unrestricted interaction possibilities represent a realistic environment, the knowledge of the agents in our approach is limited to local information and their possible interaction is defined by a contact graph
We consider that centralized techniques are not best suited for searching transaction sequences leading to an optimal allocation
Summary
In the past few years, an increasing number of studies focused on resource allocation problems, either from a centralized or a distributed point of view. At the opposite, distributed solving techniques consider that resources are initially allocated between agents, and the aim is to determine a sequence of transactions leading to an optimal allocation. Most of these techniques cannot be used in practice: either they do not consider some constraints inherent to the application context or they rely on unrealistic assumptions. One of them, called social efficiency, can be measured owing to notions from the social choice theory (Moulin, 1988; Arrow et al, 2002) These notions evaluate different aspects of allocations in a global way, aggregating the satisfaction of all the agents. These four welfare notions are the most important and the most widely used to date (Endriss et al, 2006; Chevaleyre et al, 2010; Ramezani & Endriss, 2009; Brams & Taylor, 1996) and only those will be considered in this paper for this reason
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