The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. Theoretical formalizations of such agents and their implementations have proceeded in parallel with little or no connection between them. This paper explores a particular type of rational agent, a BeliefDesire -Intention (BDI) agent. The primary aim of this paper is to integrate (a) the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective; (b) the implementations of BDI agents from an ideal theoretical perspective and a more practical perspective; and (c) the building of large-scale applications based on BDI agents. In particular, an air-traffic management application will be described from both a theoretical and an implementation perspective.

The formalization of multi-agent autonomous systems requires a rich ontology for capturing a variety of collective behaviours and a powerful semantics for distinguishing between collective agents having, executing, and jointly intending a plan. In this paper, we introduce the notion of social agents and social plans. A definition of joint intentions is provided that avoids some of the problems encountered by previous formalizations. In particular, it models cooperation by requiring that agents adopt a joint goal and a joint plan of action before forming a joint intention. The paper also stresses the planning capability of agents and outlines a process for means-end reasoning by multiple agents. 1 Introduction Situated agents are systems embedded in dynamic environments; they continuously sense their environment and effect changes to it by performing actions. These agents have to balance the time they devote to thinking against the time they take acting. Also they need to balance the...

The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. A number of theoretical formalizations for such multiagent systems have been proposed. However, most of these formalizations do not have a strong semantic basis nor a sound and complete axiomatization. Hence, it has not been clear as to how these formalizations could be used in building agents in practice. This paper explores a particular type of multi-agent system, in which each agent is viewed as having the three mental attitudes of belief (B), desire (D), and intention (I). It provides a family of multi-modal branching-time BDI logics with a semantics that is grounded in traditional decision theory and a possible-worlds framework, categorizes them, provides sound and complete axiomatizations, and gives constructive tableaubased decision procedures for testing the satisfiability and validity of formulas. The computational complexity of these decision procedures is n...

We investigate the semantic foundations of a method for modeling agents as entities with a mental state which was suggested by McCarthy and by Newell. Our goals are to formalize this modeling approach and its semantics, to understand the theoretical and practical issues that it raises, and to address some of them. In particular, this requires specifying the model's parameters and how these parameters are to be assigned (i.e., their grounding). We propose a basic model in which the agent is viewed as a qualitative decision maker with beliefs, preferences, and decision strategy; and we show how these components would determine the agent's behavior. We ground this model in the agent's interaction with the world, namely, in its actions. This is done by viewing model construction as a constraint satisfaction problem in which we search for a model consistent with the agent's behavior and with our general background knowledge. In addition, we investigate the conditions under which a mental st...

The specification, design, and verification of agent-oriented systems depends upon having clear, intuitive formalisms for reasoning about the properties of such systems. In this paper, we consider agents whose state comprises the three mental attitudes of belief, desire, and intention. While the static relationships among these entities has had considerable attention, the manner in which these entities change over time has not been formalized rigourously. By considering some simple examples, we show that the formalization of some of these intuitions is problematic. We then examine these intuitions from a possible-worlds perspective and formally describe the dynamics of intention maintenance in the context of changing beliefs and desires. To solve the problems identified in the examples, and to properly capture our semantic intuitions about intention maintenance, we extend the standard logics by introducing forms for only modalities of belief, desire, and intention, along the lines of Levesque's only believe operator. This allows us to formalize the process of intention maintenance. We conclude by comparing our work with other related work.

In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents' preferences via past interactions. Over time, the agents can incrementally update their models of other agents' preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complement knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situations where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy). Introduction Multiagent systems are networks of loosely-coupled comp...

An important aspect of agent autonomy is the decision making capability of the agents. We discuss several issues that agents need to deliberate about in order to decide which action to perform. We assume that there is no unique (rational or universal) deliberation process and that the deliberation process can be specified in various ways. The deliberation process is investigated from two perspectives. From the agent specification point of view the deliberation process can be specified by dynamic properties such as commitment strategies, and from the agent programming point of view the deliberation process should be implemented through the deliberation cycle of the agent, which can be either fixed or determined by a deliberation programming language.

Abstract—We consider a common task in multiagent systems where agents need to estimate the state of an uncertain domain so that they can act accordingly. If each agent only has partial knowledge about the domain and local observations, how can the agents accomplish the task with a limited amount of communication? Multiply sectioned Bayesian networks (MSBNs) provide an effective and exact framework for such a task but also impose a set of constraints. Are there simpler frameworks with the same performance but with less constraints? We identify a small set of high level choices which logically imply the key representational choices leading to MSBNs. The result addresses the necessity of constraints of the framework. It facilitates comparisons with related frameworks and provides guidance to potential extensions of the framework. (Keywords: multiagent system, decentralized interpretation, communication, organization structure, uncertain reasoning, probabilistic reasoning, belief network, Bayesian network) I.

In this paper we investigate the specification and verification of information systems with an organizational structure. Such systems are modelled as a normative multiagent system. To this end we use KBDIO CTL , an extension of BDI CTL in which obligations and permissions are represented by directed modal operators. We illustrate how the logic can be used by introducing and discussing various properties of normative systems and individual agents which can be represented in the logic. In particular we discuss the enforcement of norms.

This paper summarises our on-going work on mixed-initiative decision making which extends both classical decision theory and a symbolic theory of decision making based on argumentation to a multi-agent domain.