Patricia Everaere

The strategy-proofness landscape of merging

Merging operators aim at defining the beliefs/goals of a group of agents from the beliefs/goals of each member of the group. Whenever an agent of the group has preferences over the possible results of the merging process (i.e., the possible merged bases), she can try to rig the merging process by lying on her true beliefs/goals if this leads to a better merged base according to her point of view. Obviously, strategy-proof operators are highly desirable in order to guarantee equity among agents even when some of them are not sincere. In this paper, we draw the strategy-proof landscape for many merging operators from the literature, including model-based ones and formula-based ones. Both the general case and several restrictions on the merging process are considered.

Disjunctive merging: Quota and Gmin merging operators

When aggregating information from a group of agents, accepting the pieces of information shared by all agents is a natural requirement. In this paper, we investigate such a unanimity condition in the setting of propositional merging. We discuss two interpretations of the unanimity condition. We show that the first interpretation is captured by existing postulates for merging. But the second interpretation is not, and this leads to the introduction of a new disjunction postulate (Disj). It turns out that existing operators satisfying (Disj) do not perform well with respect to the standard criteria used to evaluate merging operators: logical properties, computational complexity and strategy-proofness. To fill this gap, we introduce two new families of propositional merging operators, quota operators and Gmin operators, which satisfy (Disj), and achieve interesting trade-offs with respect to the logical, computational, and strategy-proofness criteria.

Distributed architectures for electronic cash schemes: a survey

The volume of E-commerce transactions has considerably increased in the last several years. One of the most important aspects of such progress is the efforts made to develop and deploy dependable a...The volume of E-commerce transactions has considerably increased in the last several years. One of the most important aspects of such progress is the efforts made to develop and deploy dependable and secure payment infrastructures. Among these infrastructures is electronic cash, which is an attempt to reproduce the characteristics of paper cash in online transactions. Electronic cash schemes have so far been the purpose of a significant amount of research work. Although real-life deployments of such schemes are expected to take place in highly distributed environments, limited attention has been paid in the literature on underlying architectural issues. So far the focus has mostly been on addressing only security issues. However, for real-life deployment, distributed processing criteria such as performance, scalability and availability are of prime importance. In this paper, through a survey of the literature, we identify and analyse the different distributed architectural styles underlying existing e-cash schemes. We discuss the strengths and limitations of these architectures with respect to fundamental system distribution criteria. In light of such discussion, we make some recommendations for designing effective distributed e-cash systems from an architectural perspective.

Double spending protection for e-cash based on risk management

Electronic cash is an attempt to replace and reproduce paper cash in electronic transactions that faces competing challenges when used either online or offline. In effect, while effective protection against double spending for e-cash can be achieved in online payment environments through real-time detection, this comes at the expense of efficiency, the bank representing in such case a performance bottleneck and single point of failure. In contrast, in offline payment environments, while efficiency is improved, double spending can be detected only after the fact, which can be very costly. We propose in this paper a risk management approach for double spending protection which allows suitable tradeoffs between efficiency and effectiveness. This involves using the service of a trader, who is a trusted third party that will cover the risk involved in offline payment transactions, against some remuneration. The main goal is to provide full coverage to users against losses related to invalid coins while avoiding or minimizing interactions with the bank. Since the trader will incur some risk by guaranteeing coins while she cannot communicate with the bank, a winning strategy is devised for the trader to mitigate such risk.

Nash Welfare Allocation Problems: Concrete Issues

The allocation of m resources between n agents is an AI problem with a great practical interest for automated trading. The general question is how to configure the behavior of bargaining agents to induce a socially optimal allocation. The literature contains many proposals for calculating a social welfare but the Nash welfare seems to be the one which has the most interesting properties for a fair agent society. It guarantees that all resources are fairly distributed among agents respecting their own preferences. This article shows first that the computation of this welfare is a difficult problem, contrary to common intuition. Many counter-examples describe the pitfalls of this resolution. In a second step, we describe our distributed multi-agent solution based on a specific agent’sbehavior and the results we get on difficult instances. We finally claim that this anytime solution is the only one able to effectively address this problem of obvious practical interest.

Propositional merging and judgment aggregation: two compatible approaches?

There are two theories of aggregation of logical formulae: merging and judgment aggregation. In this work we investigate the relationships between these theories; one of our objectives is to point out some correspondences/discrepancies between the associated rationality properties.

Problèmes d'allocation de ressources et bien-être de Nash. Résolution par négociation entre agents

RÉSUMÉ. Allouer m ressources entre n agents, de façon à optimiser leur bien-être, est un problème qui peut souvent être résolu de manière centralisée. Cependant, pour certaines fonctions de bien-être social, une résolution centralisée n’est pas envisageable. Par exemple, le bien-être de Nash est une fonction qui a d’indéniables qualités mais qui ne peut être optimisée de manière classique. De plus, de nombreuses applications reposent sur des hypothèses qui ne peuvent pas être prises en compte par ces techniques centralisées alors que d’autres méthodes le permettent, comme les approches multi-agents. Après une présentation du problème multi-agents d’allocation de ressources, nous mettons en évidence les difficultés liées aux techniques centralisées et distribuées existantes. Nous proposons une méthode s’appuyant sur la notion de transaction sociale que nous revendiquons être la seule méthode « anytime » capable de résoudre efficacement le problème d’allocation de Nash.