We introduce a natural variant of weighted voting games, which we refer to as k-Prize Weighted Voting Games. Such games consist of n players with weights, and k prizes, of possibly differing values. The players form coalitions, and the i-th largest coalition (by the sum of weights of its members) wins the i-th largest prize, which is then shared among its members. We present four solution concepts to analyse the games in this class, and characterise the existence of stable outcomes in games with three players and two prizes, and in games with uniform prizes. We then explore the efficiency of stable outcomes in terms of Pareto optimality and utilitarian social welfare. Finally, we study the computational complexity of finding stable outcomes.

Multi-agent influence diagrams (MAIDs) are a popular game-theoretic model based on Bayesian networks. In some settings, MAIDs offer significant advantages over extensive-form game representations. Previous work on MAIDs has assumed that agents employ behavioural policies, which set independent conditional probability distributions over actions for each of their decisions. In settings with imperfect recall, however, a Nash equilibrium in behavioural policies may not exist. We overcome this by showing how to solve MAIDs with forgetful and absent-minded agents using mixed policies and two types of correlated equilibrium. We also analyse the computational complexity of key decision problems in MAIDs, and explore tractable cases. Finally, we describe applications of MAIDs to Markov games and team situations, where imperfect recall is often unavoidable.

We introduce a non-cooperative game model in which players’ decision nodes are partially ordered by a dependence relation, which directly captures informational dependencies in the game. In saying that a decision node v is dependent on decision nodes v1,…,vk, we mean that the information available to a strategy making a choice at v is precisely the choices that were made at v1,…,vk. Although partial order games are no more expressive than extensive form games of imperfect information (we show that any partial order game can be reduced to a strategically equivalent extensive form game of imperfect information, though possibly at the cost of an exponential blowup in the size of the game), they provide a more natural and compact representation for many strategic settings of interest. After introducing the game model, we investigate the relationship to extensive form games of imperfect information, the problem of computing Nash equilibria, and conditions that enable backwards induction in this new model.

We study political parties that strategically place their candidates in districts so to maximise the number of their nominees that get elected. In each district, voters rank the nominated candidates and elect the plurality winners. After studying equilibrium existence in restricted instances, we show that deciding the existence of pure Nash equilibria for these games is NP-complete if party size is bounded by a constant and Σ^P _2-complete for the general case. For the hardness part of the latter result we reduce from \EEthreeSAT.

We present a model for the strategic selection of party nominees, where competing groups choose their representatives based on the expected electoral returns. Technically, we look at a generalisation of the Hotelling-Downs model, where each nominee has a predefined position on the political spectrum and attracts the closest voters compared to all other representatives. Within this framework we explore the algorithmic properties of Nash equilibria, which are not guaranteed to exist even in two party competitions. We show that finding a Nash equilibrium is NP-complete for the general case. However, if there are only two competing parties, this can be achieved in linear time. The results readily extend to games with restricted positioning options for the players involved, such as facility location and Voronoi games.

We provide a survey of the state of the art of rational verification : the problem of checking whether a given temporal logic formula ϕ is satisfied in some or all game-theoretic equilibria of a multi-agent system – that is, whether the system will exhibit the behavior ϕ represents under the assumption that agents within the system act rationally in pursuit of their preferences. After motivating and introducing the overall framework of rational verification, we discuss key results obtained in the past few years as well as relevant related work in logic, AI, and computer science.

This paper studies the computation of mixed Nash equilibria in weighted Boolean games. In weighted Boolean games, players aim to maximise the total expected weight of a set of formulas by selecting behavioural strategies, that is, randomisations over the truth assignments for each propositional variable under their unique control. Behavioural strategies thus present a compact representation of mixed strategies. Two results are algorithmically significant: (a) behavioural equilibria satisfy a specific independence property; and (b) they allow for exponentially fewer supports than mixed equilibria. These findings suggest two ways in which one can leverage existing algorithms and heuristics for computing mixed equilibria: a naive approach where we check mixed equilibria for the aforesaid independence property, and a more sophisticated approach based on support enumeration. In addition, we explore a direct numerical approach inspired by finding correlated equilibria using linear programming. In an extensive experimental study, we compare the performance of these three approaches.

We introduce and investigate a novel notion of expressiveness for temporal logics that is based on game theoretic properties of multi-agent systems. We focus on iterated Boolean games, where each agent i has a goal γai, represented using (a fragment of) Linear Temporal Logic (LTL). The goal γai captures agent i's preferences: the models of γi represent system behaviours that would satisfy i, and each player is assumed to act strategically, taking into account the goals of other players, in order to bring about computations satisfying their goal. In this setting, we apply the standard game-theoretic concept of Nash equilibria: the Nash equilibria of an iterated Boolean game can be understood as a (possibly empty) set of computations, each computation representing one way the system could evolve if players chose strategies in Nash equilibrium. Such an equilibrium set of computations can be understood as expressing a temporal property---which may or may not be expressible within a particular LTL fragment. The new notion of expressiveness that we study is then as follows: what LTL properties are characterised by the Nash equilibria of games in which agent goals are expressed in fragments of LTL? We formally define and investigate this notion of expressiveness and some related issues, for a range of LTL fragments.

In 1998 a long-lost proposal for an election law by Gottlob Frege (1848–1925) was rediscovered in the Thüringer Universitäts- und Landesbibliothek in Jena, Germany. The method that Frege proposed for the election of representatives of a constituency features a remarkable concern for the representation of minorities. Its core idea is that votes cast for unelected candidates are carried over to the next election, while elected candidates incur a cost of winning. We prove that this sensitivity to past elections guarantees a proportional representation of political opinions in the long run. We find that through a slight modification of Frege’s original method even stronger proportionality guarantees can be achieved. This modified version of Frege’s method also provides a novel solution to the apportionment problem, which is distinct from all of the best-known apportionment methods, while still possessing noteworthy proportionality properties.

Game theory provides a well-established framework for the analysis of concurrent and multi-agent systems. The basic idea is that concurrent processes (agents) can be understood as corresponding to players in a game; plays represent the possible computation runs of the system; and strategies define the behaviour of agents. Typically, strategies are modelled as functions from sequences of system states to player actions. Analysing a system in such a setting involves computing the set of (Nash) equilibria in the concurrent game. However, we show that, with respect to the above model of strategies (arguably, the "standard" model in the computer science literature), bisimilarity does not preserve the existence of Nash equilibria. Thus, two concurrent games which are behaviourally equivalent from a semantic perspective, and which from a logical perspective satisfy the same temporal logic formulae, may nevertheless have fundamentally different properties (solutions) from a game theoretic perspective. Our aim in this paper is to explore the issues raised by this discovery. After illustrating the issue by way of a motivating example, we present three models of strategies with respect to which the existence of Nash equilibria is preserved under bisimilarity. We use some of these models of strategies to provide new semantic foundations for logics for strategic reasoning, and investigate restricted scenarios where bisimilarity can be shown to preserve the existence of Nash equilibria with respect to the conventional model of strategies in the computer science literature.

Many hardness results in computational social choice use the fact that every digraph may be induced as the pairwise majority relation of some preference profile. The standard construction requires a number of voters that is almost linear in the number of alternatives and it is unclear whether hardness holds when the number of voters is bounded. In this paper, we systematically study majority digraphs inducible by a constant number of voters. First, we characterize digraphs inducible by two or three voters, and give sufficient conditions for more voters. Second, we use SAT solvers to compute the minimum number of voters required to induce digraphs given by generated and real-world preference profiles. Finally, using our sufficient conditions, we show that several voting rules remain hard to evaluate for small constant numbers of voters. Kemeny's rule remains hard for 7 voters; previous methods could only prove this for constant even numbers of voters.

Many hardness results in computational social choice use the fact that every digraph may be induced as the pairwise majority relation of some preference profile. The standard construction requires a number of voters that is almost linear in the number of alternatives and it is unclear whether hardness holds when the number of voters is bounded. In this paper, we systematically study majority digraphs inducible by a constant number of voters. First, we characterize digraphs inducible by two or three voters, and give sufficient conditions for more voters. Second, we use SAT solvers to compute the minimum number of voters required to induce digraphs given by generated and real-world preference profiles. Finally, using our sufficient conditions, we show that several voting rules remain hard to evaluate for small constant numbers of voters. Kemeny's rule remains hard for 7 voters; previous methods could only prove this for constant even numbers of voters.

Game theory provides a well-established framework for the analysis and verification of concurrent and multi-agent systems. Typically, the analysis of a multi-agent system involves computing the set of equilibria in the associated multi-player game representing the behaviour of the system. As systems grow larger, it becomes increasingly harder to find equilibria in the game - which represent the rationally stable behaviours of the multi-agent system (the solutions of the game). To address this issue, in this paper, we study the concept of local equilibria, which are defined with respect to (maximal) stable coalitions of agents for which an equilibrium can de found. We focus on the solutions given by the Nash equilibria of Boolean games and iterated Boolean games, two logic-based models for multi-agent systems, in which the players' goals are given by formulae of propositional logic and LTL, respectively.

Some game-theoretic solution concepts such as the Shapley value and the Banzhaf index have recently gained popularity as measures of node centrality in networks. While this direction of research is promising, the computational problems that surround it are challenging and have largely been left open. To date there are only a few positive results in the literature, which show that some game-theoretic extensions of degree-, closeness- and betweenness-centrality measures are computable in polynomial time, i.e., without the need to enumerate the exponential number of all possible coalitions. In this article, we show that these results can be extended to a much larger class of centrality measures that are based on a family of solution concepts known as semivalues. The family of semivalues includes, among others, the Shapley value and the Banzhaf index. To this end, we present a generic framework for defining game-theoretic network centralities and prove that all centrality measures that can be expressed in this framework are computable in polynomial time. Using our framework, we present a number of new and polynomial-time computable game-theoretic centrality measures.

An important subclass of social choice functions, so-called majoritarian (or C1) functions, only take into account the pairwise majority relation between alternatives. In the absence of majority ties-e.g., when there is an odd number of agents with linear preferences-the majority relation is antisymmetric and complete and can thus conveniently be represented by a tournament. Tournaments have a rich mathematical theory and many formal results for majoritarian functions assume that the majority relation constitutes a tournament. Moreover, most majoritarian functions have only been defined for tournaments and allow for a variety of generalizations to unrestricted preference profiles, none of which can be seen as the unequivocal extension of the original function. In this paper, we argue that restricting attention to tournaments is justified by the existence of a conservative extension, which inherits most of the commonly considered properties from its underlying tournament solution.

The work we present in this paper initiated the formal study of fractional hedonic games, coalition formation games in which the utility of a player is the average value he ascribes to the members of his coalition. Among other settings, this covers situations in which players only distinguish between friends and non-friends and desire to be in a coalition in which the fraction of friends is maximal. Fractional hedonic games thus not only constitute a natural class of succinctly representable coalition formation games, but also provide an interesting framework for network clustering. We propose a number of conditions under which the core of fractional hedonic games is non-empty and provide algorithms for computing a core stable outcome. By contrast, we show that the core may be empty in other cases, and that it is computationally hard in general to decide non-emptiness of the core.

Boolean games are logic-based games in which each player desires the satisfaction of a propositional logic goal, and in which the pure strategies available to a player are the possible truth assignments to a set of propositional variables under that player’s unique control. In this setting, a mixed strategy for a player is a probability distribution over the possible valuations to that player’s variables. Unfortunately, the obvious representation of such a mixed strategy is of size exponential in the number of variables a player controls. In this paper, we consider a compact alternative model, behavioural strategies, in which randomisation takes place at the level of the propositional variables. We characterise behavioural strategies as a subset of mixed strategies and provide a detailed analysis of Nash equilibria in behavioural strategies, along with an algorithm for enumerating them in non-degenerate two-player Boolean games that runs polynomially in the number of outcomes.

The existence of (Nash) equilibria with undesirable properties is a well-known problem in game theory, which has motivated much research directed at the possibility of mechanisms for modifying games in order to eliminate undesirable equilibria, or induce desirable ones. Taxation schemes are a well-known mechanism for modifying games in this way. In the multi-agent systems community, taxation mechanisms for incentive engineering have been studied in the context of Boolean games with costs. These are games in which each player assigns truth-values to a set of propositional variables she uniquely controls in pursuit of satisfying an individual propositional goal formula; different choices for the player are also associated with different costs. In such a game, each player prefers primarily to see the satisfaction of their goal, and secondarily, to minimise the cost of their choice, thereby giving rise to lexicographic preferences over goal-satisfaction and costs. Within this setting, where taxes operate on costs only, however, it may well happen that the elimination or introduction of equilibria can only be achieved at the cost of simultaneously introducing less desirable equilibria or eliminating more attractive ones. Although this framework has been studied extensively, the problem of precisely characterising the equilibria that may be induced or eliminated has remained open. In this paper we close this problem, giving a complete characterisation of those mechanisms that can induce a set of outcomes of the game to be exactly the set of Nash Equilibrium outcomes.

In this paper we study techniques for reasoning about game-like concurrent systems, where the components of the system act rationally and strategically in pursuit of logically-specified goals. Specifically, we start by presenting a computational model for such concurrent systems, and investigate its computational, mathematical, and game-theoretic properties. We then define and investigate a branching-time temporal logic for reasoning about the equilibrium properties of game-like concurrent systems. The key operator in this temporal logic is a novel path quantifier [NE]φ, which asserts that φ holds on all Nash equilibrium computations of the system.

A fundamental problem in game theory is the possibility of reaching equilibrium outcomes with undesirable properties, e.g., inefficiency. The economics literature abounds with models that attempt to modify games in order to avoid such undesirable properties, for example through the use of subsidies and taxation, or by allowing players to undergo a bargaining phase before their decision. In this paper, we consider the effect of such transformations in Boolean games with costs, where players control propositional variables that they can set to true or false, and are primarily motivated to seek the satisfaction of some goal formula, while secondarily motivated to minimise the costs of their actions. We adopt (pure) preparation sets (prep sets) as our basic solution concept. A preparation set is a set of outcomes that contains for every player at least one best response to every outcome in the set. Prep sets are well-suited to the analysis of Boolean games, because we can naturally represent prep sets as propositional formulas, which in turn allows us to refer to prep formulas . The preference structure of Boolean games with costs makes it possible to distinguish between hard and soft prep sets. The hard prep sets of a game are sets of valuations that would be prep sets in that game no matter what the cost function of the game was. The properties defined by hard prep sets typically relate to goal-seeking behaviour, and as such these properties cannot be eliminated from games by, for example, taxation or subsidies. In contrast, soft prep sets can be eliminated by an appropriate system of incentives. Besides considering what can happen in a game by unrestricted manipulation of players’ cost function, we also investigate several mechanisms that allow groups of players to form coalitions and eliminate undesirable outcomes from the game, even when taxes or subsidies are not a possibility.