This paper introduces AgentSpeak(F), a variation of the BDI logic programming language AgentSpeak(L) intended to permit the model-theoretic verification of multi-agent systems. After briefly introducing AgentSpeak(F) and discussing its relationship to AgentSpeak(L), we show how AgentSpeak(F) programs can be transformed into Promela, the model specification language for the Spin model-checking system. We also describe how specifications written in a simplified form of BDI logic can be transformed into Spin-format linear temporal logic formul. With our approach, it is thus possible to automatically verify whether or not multi-agent systems implemented in AgentSpeak(F) satisfy specifications expressed as BDI logic formul. We illustrate our approach with a short case study, in which we show how BDI properties of a simulated auction system implemented in AgentSpeak(F) were verified.

In this paper we introduce a formal framework for the construction of normative multiagent systems, based on Searle's notion of the construction of social reality. Within the structure of normative multiagent systems we distinguish between regulative norms that describe obligations, prohibitions and permissions, and constitutive norms that regulate the creation of institutional facts as well as the modification of the normative system itself. Using the metaphor of normative systems as agents, we attribute mental attitudes to the normative system. In particular,

Introduction Within the ATAL community, the belief-desire-intention (BDI) model has come to be possibly the best known and best studied model of practical reasoning agents. There are several reasons for its success, but perhaps the most compelling are that the BDI model combines a respectable philosophical model of human practical reasoning, (originally developed by Michael Bratman [1]), a number of implementations (in the IRMA architecture [2] and the various PRS-like systems currently available [7]), several successful applications (including the now-famous fault diagnosis system for the space shuttle, as well as factory process control systems and business process management [8]), and finally, an elegant abstract logical semantics, which have been taken up and elaborated upon widely within the agent research community [14, 16]. However, it could be argued that the BDI model is now becoming somewhat dated: the principles of the architecture were established in the mid-1980s,

MABLE is a language for the design and automatic verification of multi-agent systems. MABLE is essentially a conventional imperative programming language, enriched by constructs from the agent-oriented programming paradigm. A MABLE system contains a number of agents, programmed using the MABLE imperative programming language. Agents in MABLE have a mental state consisting of beliefs, desires and intentions. Agents communicate using request and inform performatives, in the style of the FIPA agent communication language. MABLE systems may be augmented by the addition of formal claims about the system, expressed using a quantified, linear temporal belief-desire-intention logic. MABLE has been fully implemented, and makes use of the SPIN model checker to automatically verify the truth or falsity of claims.

An important concept for intelligent agent systems is goals. Goals have two aspects: declarative (a description of the state sought), and procedural (a set of plans for achieving the goal). A declarative view of goals is necessary in order to reason about important properties of goals, while a procedural view of goals is necessary to ensure that goals can be achieved efficiently in dynamic environments. In this paper we propose a framework for goals which integrates both views. We discuss the requisite properties of goals and the link between the declarative and procedural aspects, then derive a formal semantics which has these properties. We present a high-level plan notation with goals and give its formal semantics.

We present a framework for verifying temporal and epistemic properties of multi-agent systems by means of bounded model checking. We use interpreted systems as underlying semantics. We give details of the proposed technique, and show how it can be applied to the "attacking generals problem ", a typical example of coordination in multi-agent systems.

We present a model of cooperative problem solving that describes the process from its beginning, with some agent recognising the potential for cooperation with respect to one of its goals, through to team action. Our approach is to characterise the mental states of the agents that leads them to solicit, and take part in, cooperative action. The model is formalised by expressing it as a theory in a quantified multi-modal logic.

Rational agents are important objects of study in several research communities, including economics, philosophy, cognitive science, and most recently computer science and artificial intelligence. Crudely, a rational agent is an entity that is capable of acting on its environment, and which chooses to act in such a way as to further its own best interests. There has recently been much interest in the use of mathematical logic for developing formal theories of such agents. Such theories view agents as practical reasoning systems, deciding moment by moment which action to perform nexi, given the beliefs they have about the world and their desires with respect to how they would like the world to be. In this article, we survey the state of the art in developing logical theories of rational agency. Following a discussion on the dimensions along which such theories can vary, we briefly survey the logical tools available in order to construct such theories. We then review and critically assess three of the best known theories of rational agency: Cohen and Levesque's intention logic, Rao and Georgeff's BDI logics, and the KARO framework of Meyer et al. We then discuss the various roles that such logics can play in helping us to engineer rational agents, and conclude with a discussion of open problems.

In this paper, I motivate, define, and illustrate the notion of computationally grounded theories of agency. A theory of agency is said to be computationally grounded if we can give the theory an interpretation in terms of some concrete computational model. This requirement is essential if we are to claim that the theories we develop can be understood as expressing properties of real multiagent systems. After introducing and formally defining the concept of a computationally grounded theory of agency, I illustrate the idea with reference to ¡£¢¥¤ logic, a formalism for reasoning about agent systems that has a semantics defined with respect to an automata-like model of agents. ¡£¢¦¤

Abstract. This paper gives an overview of our recent work on an approach to verifying multi-agent programs. We automatically translate multi-agent systems programmed in the logic-based agent-oriented programming language AgentSpeak into either Promela or Java, and then use the associated Spin and JPF model checkers to verify the resulting systems. We also describe the simplified BDI logical language that is used to write the properties we want the systems to satisfy. The approach is illustrated by means of a simple case study.