We consider a framework for preference aggregation on multiple binary issues, where agents' preferences are represented by (possibly cyclic) CP-nets. We focus on the majority aggregation of the individual CP-nets, which is the CP-net where the direction of each edge of the hypercube is decided according to the majority rule. First we focus on hypercube Condorcet winners (HCWs); in particular, we show that, assuming a uniform distribution for the CP-nets, the probability that there exists at least one HCW is at least 1-1/e, and the expected number of HCWs is 1. Our experimental results confirm these results. We also show experimental results under the Impartial Culture assumption. We then generalize a few tournament solutions to select winners from (weighted) majoritarian CP-nets, namely Copeland, maximin, and Kemeny. For each of these, we address some social choice theoretic and computational issues.

The social lending market, with over a billion dollars in loans, is a two-sided matching market where borrowers specify demands and lenders specify total budgets and their desired interest rates from each acceptable borrower. Because different borrowers correspond to different risk-return profiles, lenders have preferences over acceptable borrowers; a borrower prefers lenders in order of the interest rates they offer to her. We investigate the question of what is a computationally feasible, 'good', allocation to clear this market. We design a strongly polynomial time algorithm for computing a Pareto-efficient stable outcome in a two-sided many-to-many matching market within differences, and use this to compute an allocation for the social lending market that satisfies the properties of stability — a standard notion of fairness in two-sided matching markets — and Pareto efficiency; and additionally addresses envy-freeness amongst similar borrowers and risk diversification for lenders.

Gjerstad and Dickhaut, 1998; Nicolaisen et al., 2001] and a market selection strategy which is mainly based on the history This paper describes the strategies used by of the trader's profit made with each specialist. AstonCAT-Plus, the post-tournament version of A CAT game lasts a number of days (500 days in CATthe specialist designed for the TAC Market Design 2010). Each day consists of a number of trading rounds, Tournament 2010. It details how AstonCATwhich each lasts for a known constant length of time. The Plus accepts shouts, clears market, sets transaction daily evaluation of the specialists is based on three metrics: prices and charges fees. Through empirical evaluation, (1) market share, which is the percentage of the total traders' we show that AstonCAT-Plus not only outperforms population registered in the market; (2) profit share, which is AstonCAT (tournament version) significantly the ratio of the daily profit a specialist obtains to the profit of but also achieves the second best overall all specialists and (3) transaction success rate (TSR), which score against some top entrants of the competition.

In this paper we propose a mechanism that encourages agents, participating in an open MAS, to follow a desirable behaviour, by introducing modifications in the environment. This mechanism is deployed by using an infrastructure based on institutional agents called incentivators. Each external agent is assigned to an incentivator that is able to discover its preferences, and to learn the suitable modifications in the environment, in order to improve the global utility of a system in response to inadequate design or changes in the population of participating agents. The mechanism is evaluated in a p2p scenario.

Given an argumentation framework and a group of agents, the individuals may have divergent opinions on the status of the arguments. If the group needsto reach a common position on the argumentation framework, the question is how the individual evaluations can be mapped into a collective one. Thisproblem has been recently investigated by Caminada and Pigozzi. In this paper, we investigate the behaviour of two of such operators from a socialchoice-theoretic point of view. In particular, we study under which conditions these operators are Pareto optimal and whether they are manipulable.

Trust is crucial in dynamic multi-agent systems, where agents may frequently join and leave, and the structure of the society may often change. In these environments, it may be difficult for agents to form stable trust relationships necessary for confident interactions. Societies may break down when trust between agents is too low to motivate interactions. In such settings, agents should make decisions about who to interact with, given their degree of trust in the available partners. We propose a decision-theoretic model of trust decision making allows controls to be used, as well as trust, to increase confidence in initial interactions. We consider explicit incentives, monitoring and reputation as examples of such controls. We evaluate our approach within a simulated, highly-dynamic multi-agent environment, and show how this model supports the making of delegation decisions when trust is low.

Alternating-time temporal logic (ATL) is a well-known logic for reasoning about strategic abilities of agents. An important feature that distinguishes variants of ATL for imperfect information scenarios is that the standard fixed point characterizations of temporal modalities do not hold anymore. In this paper, we show that adding explicit fixed point operators to the "next-time" fragment of ATL already allows to capture abilities that could not be expressed in ATL. We also illustrate that the new language allows to specify important kinds of abilities, namely ones where the agents can always recompute their strategy while executing it. Thus, the agents are not assumed to remember their strategy by definition, like in the existing variants of ATL. Last but not least, we show that verification of such abilities can be cheaper than for all the variants of `"ATL with imperfect information" considered so far.

The environment is an essential component of multi-agent systems and is often used to coordinate the behaviour of individualagents. Recently many languages have been proposed to specify and implement multi-agent environments in terms of social and normative concepts. In this paper, we first introduce a formal setting of multi-agent environment which abstracts from concrete specification languages. We extend this formal setting with norms and sanctions and show how concepts from mechanism design can be used to formally analyse and verify whether specific normative behaviours can be enforced (or implemented) if agents follow their subjective preferences. We also consider complexity issues of associated problems.

An important problem in voting is that agents may misrepresent their preferences in order to obtain a more preferred outcome. Unfortunately, this phenomenon has been shown to be inevitable in the case of resolute, i.e., single-valued, social choice functions. In this paper, we introduce a variant of Maskin-monotonicity that completely characterizes the class of pairwise irresolute social choice functions that are group-strategyproof according to Kelly's preference extension.The class is narrow but contains a number of appealing Condorcet extensions such as the minimal covering set and the bipartisan set, thereby answering a question raised independently by Barbera (1977) and Kelly (1977). These functions furthermore encourage participation and thus do not suffer from the no-show paradox (under Kelly's extension).

We consider the following sequential allocation process. A benevolent central authority has to allocate a set of indivisible goods to a set of agents whose preferences it is totally ignorant of. We consider the process of allocating objects one after the other by designating an agent and asking her to pick one of the objects among those that remain. The problem consists in choosing the "best" sequence of agents, according to some optimality criterion. We assume that agents have additive preferences over objects. The choice of an optimality criterion depends on three parameters: how utilities of objects are related to their ranking in an agent's preference relation; how the preferences of different agents are correlated; and how social welfare is defined from the agents' utilities. We address the computation of a sequence maximizing expected social welfare under several assumptions. We also address strategical issues.