Since it was first proposed by Moses, Shoham, and Tennenholtz, the social laws paradigm has proved to be one of the most compelling approaches to the offline coordination of multiagent systems. In this paper, we make four key contributions to the theory and practice of social laws in multiagent systems. First, we show that the Alternating-time Temporal Logic (atl) of Alur, Henzinger, and Kupferman provides an elegant and powerful framework within which to express and understand social laws for multiagent systems. Second, we show that the effectiveness, feasibility, and synthesis problems for social laws may naturally be framed as atl model checking problems, and that as a consequence, existing atl model checkers may be applied to these problems. Third, we show that the complexity of the feasibility problem in our framework is no more complex in the general case than that of the corresponding problem in the Shoham–Tennenholtz framework (it is np-complete). Finally, we show how our basic framework can easily be extended to permit social laws in which constraints on the legality or otherwise of some action may be explicitly required. We illustrate the concepts and techniques developed by means of a running example.

Electronic markets, dispute resolution and negotiation protocols are three types of application domains that can be viewed as open agent societies. Key characteristics of such societies are agent heterogeneity, conflicting individual goals and unpredictable behaviour. Members of such societies may fail to, or even choose not to, conform to the norms governing their interactions. It has been argued that systems of this type should have a formal, declarative, verifiable, and meaningful semantics. We present a theoretical and computational framework being developed for the executable specification of open agent societies. We adopt an external perspective and view societies as instances of normative systems. In this paper we demonstrate how the framework can be applied to specifying and executing a contract-net protocol. The specification is formalised in two action languages, the C+ language and the Event Calculus, and executed using respective software implementations, the Causal Calculator and the Society Visualiser. We evaluate our executable specification in the light of the presented case study, discussing the strengths and weaknesses of the employed action languages for the specification of open agent societies.

This paper discusses an interested party who wishes to influence the behavior of agents in a game (multi-agent interaction), which is not under his control. The interested party cannot design a new game, cannot enforce agents' behavior, cannot enforce payments by the agents, and cannot prohibit strategies available to the agents. However, he can influence the outcome of the game by committing to non-negative monetary transfers for the di#erent strategy profiles that may be selected by the agents. The interested party assumes that agents are rational in the commonly agreed sense that they do not use dominated strategies. Hence, a certain subset of outcomes is implemented in a given game if by adding nonnegative payments, rational players will necessarily produce an outcome in this subset. Obviously, by making su#ciently big payments one can implement any desirable outcome. The question is what is the cost of implementation? In this paper we introduce the notion of k-implementation of a desired set of strategy profiles, where k stands for the amount of payment that need to be actually made in order to implement desirable outcomes. A major point in k-implementation is that monetary o#ers need not necessarily materialize when following desired behaviors. We define and study k-implementation in the contexts of games with complete and incomplete information. In the latter case we mainly focus on the VCG games. Our setting is later extended to deal with mixed strategies using correlation devices. Together, the paper introduces and studies the implementation of desirable outcomes by a reliable party who cannot modify game rules (i.e. provide protocols), complementing previous work in mechanism design, while making it more applicable to many realistic CS settings.

Abstract. Electronic institutions (EIs) have been proposed as a means of regulating open agent societies. EIs define the rules of the game in agent societies by fixing what agents are permitted and forbidden to do and under what circumstances. And yet, there is the need for EIs to adapt their regulations to comply with their goals despite coping with varying populations of self-interested external agents. In this paper we focus on the extension of EIs with autonomic capabilities to allow them to yield a dynamical answer to changing circumstances through norm adaptation and changes in institutional agents.

Distributed systems are characterized by having partial observability of the global state during execution. Nevertheless, when these systems comprise cooperative agents, they should attain global objectives. Planning for these decentralized systems is a very complex task. Exchange of local information through communication can alleviate this complexity by allowing the agents to be synchronized from time to time. Due to costs associated with real-world communication, agents may not be able to continuously obtain full observability of the system. We examine mechanisms that result in the decomposition of the global problem into local simpler problems that are applied each time the agents exchange information. The communication policies are computed with respect to a given mechanism and policy of action. This paper presents a framework to study these mechanisms and evaluation criteria to compare them. We also review related work on mechanism design and compare the approaches. 1.

Abstract. Electronic institutions (EIs) have been proposed as a means of regulating open agent societies. EIs define the rules of the game in agent societies by fixing what agents are permitted and forbidden to do and under what circumstances. And yet, there is the need for EIs to adapt their regulations to comply with their goals despite coping with varying populations of self-interested agents. In this paper we focus on the extension of EIs with autonomic capabilities to alllow them to yield a dynamical answer to changing circumstances through the adaptation of their norms. 1

Power indices such as the Banzhaf index were originally developed within voting theory in an attempt to rigorously characterise the influence that a voter is able to wield in a particular voting game. In this paper, we show how such power indices can be applied to understanding the relative importance of agents when we attempt to devise a coordination mechanism using the paradigm of social laws, or normative systems. Understanding how pivotal an agent is with respect to the success of a particular social law is of benefit when designing such social laws: we might typically aim to ensure that power is distributed evenly amongst the agents in a system, to avoid bottlenecks or single points of failure. After formally defining the framework and illustrating the role of power indices in it, we investigate the complexity of computing these indices, showing that the characteristic complexity result is #P-completeness. We then investigate cases where computing indices is computationally easy.

Social law is perceived as evolving through the competition of individual social strategies held by the agents. A strategy with strong authority, accepted by many agents, will tend to diffuse to the remaining agents. The authority of a social strategy is determined by not only the number of but also the collective social positions of its overlaid agents. This paper presents a novel collective strategy diffusion model in agent social law evolution. In the model, social strategies that have strong authority are impressed on the other agents. The agents will accept (partially or in full) or reject them based on their own social strategies and social positions. The diffusion of social strategies proceeds in a series of steps and the final result depends on the interplay between the forces driving diffusion and the counteracting forces. 1

Although normative systems, or social laws, have proved to be a highly influential approach to coordination in multi-agent systems, the issue of compliance to such normative systems remains problematic. In all real systems, it is possible that some members of an agent population will not comply with the rules of a normative system, even if it is in their interests to do so. It is therefore important to consider the extent to which a normative system is robust, i.e., the extent to which it remains effective even if some agents do not comply with it. We formalise and investigate three different notions of robustness and related decision problems. We begin by considering sets of agents whose compliance is necessary and/or sufficient to guarantee the effectiveness of a normative system; we then consider quantitative approaches to robustness, where we try to identify the proportion of an agent population that must comply in order to ensure success, and finally, we consider a more general approach, where we characterise the compliance conditions required for success as a logical formula.

Abstract. In this paper, we examine the concepts of norms and roles in multiagency. After a general treatment of relationships between goals, roles, and norms in a rational utilitarian agent, we turn to team-oriented decisionmaking, which is facilitated by notions of positional role hierarchies and group roles. We use simulated Robocup as a case study for team oriented decisionmaking and illustrated role exchange as an example of team-oriented reasoning. 1