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.

In many multi-agent systems, the emergence of norms is the primary factor that determines overall behavior and utility. Agent simulations can be used to predict and study the development of these norms. However, a large number of simulations is usually required to provide an accurate depiction of the agents’ behavior, and some rare contingencies may still be overlooked completely. The cost and risk involvedwith agent simulations can be reduced by analyzing a system theoretically and producing models of its behavior. We use such a theoretical approach to examine the dynamics of a population of agents playing a coordination game to determine all the norms to which the society can converge, and develop a system of linear recurrence relations that predict how frequently each of these norms will be reached, as well as the average convergence time. This analysis produces certain guarantees about system behavior that canot be provided by a purely empirical approach, and can be used to make predictions about the emergence of norms that numerically match those obtained through large-scale simulations.

In this paper we introduce and analyze social distance games, a family of non-transferable utility coalitional games where an agent's utility is a measure of closeness to the other members of the coalition. We study both social welfare maximisation and stability in these games using a graph theoretic perspective. We use the stability gap to investigate the welfare of stable coalition structures, and propose two new solution concepts with improved welfare guarantees. We argue that social distance games are both interesting in themselves, as well as in the context of social networks.

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.

The classic Gibbard-Satterthwaite Theorem establishes that only dictatorial voting rules are strategy-proof; under any other voting rule, players have an incentive to lie about their true preferences. We consider a new approach for circumventing this result: we consider randomized voting rules that only approximate a deterministic voting rule and only are approximately strategy-proof. We show that any deterministic voting rule can be approximated by an approximately strategy-proof randomized voting rule, and we provide asymptotically tight lower bounds on the parameters required by such voting rules.

Grammatical agreement is present in many of the world's languages today and has become an essential feature that guides linguistic processing. When two words in a sentence are said to "agree", this means that they share certain features such as "gender", "number", "person" or others. The primary hypothesis of this paper is that marking agreement within one linguistic phrase reduces processing effort as phrasal constituents can more easily be recognized. The drive to reduce processing effort introduces the rise of agreement marking in a population of multiple agents by means of an incrementally aligned mapping between the most discriminatory features of a particular linguistic unit and their associative markers. A series of experiments compare feature selection methods for one-to-one agreement mappings, and show how an agreement system can be bootstrapped.

The Borda voting rule is a positional scoring rule where, for m candidates, for every vote the first candidate receives m-1 points, the second m-2 points and so on. A Borda winner is a candidate with highest total score. It has been a prominent open problem to determine the computational complexity of Unweighted Coalitional Manipulation under Borda: Can one add a certain number of additional votes (called manipulators) to an election such that a distinguished candidate becomes a winner? We settle this open problem by showing NP-hardness even for two manipulators and three input votes. Moreover, we discuss extensions and limitations of this hardness result.

Computational social choice literature has successfully studied the complexity of manipulation in variousvoting systems. However, the existing modelsof coalitional manipulation view the manipulatingcoalition as an exogenous input, ignoring thequestion of the coalition formation process. While such analysis is useful as a first approximation, a richer framework is required to model voting manipulationin the real world more accurately, and, inparticular, to explain how a manipulating coalitionarises and chooses its action. In this paper, we apply tools from cooperative game theory to developa model that considers the coalition formation processand determines which coalitions are likely toform and what actions they are likely to take. We explore the computational complexity of several standard coalitional game theory solution concepts in our setting, and study the relationship betweenour model and the classic coalitional manipulation problem as well as the now-standard bribery model.

We conduct a computational analysis of fair and optimal partitions in additively separable hedonic games. We show that, for strict preferences, a Pareto optimal partition can be found in polynomial time while verifying whether a given partition is Pareto optimal is coNP-complete, even when preferences are symmetric and strict. Moreover, computing a partition with maximum egalitarian or utilitarian social welfare or one which is both Pareto optimal and individually rational is NP-hard. We also prove that checking whether there exists a partition which is both Pareto optimal and envy-free is $\Sigma_{2}^{p}$-complete. Even though an envy-free partition and a Nash stable partition are both guaranteed to exist for symmetric preferences, checking whether there exists a partition which is both envy-free and Nash stable is NP-complete.