Our goal in this paper is to introduce and motivate a methodology, called Tropos, for building agent oriented software systems. Tropos is based on two key ideas. First, the notion of agent and all related mentalistic notions (for instance goals and plans) are used in all phases of software development, from early analysis down to the actual implementation. Second, Tropos covers also the very early phases of requirements analysis, thus allowing for a deeper understanding of the environment where the software must operate, and of the kind of interactions that should occur between software and human agents. The methodology is illustrated with the help of a case study. The Tropos language for conceptual modeling is formalized in a metamodel described with a set of UML class diagrams.

Agent systems based on the Belief, Desire and Intention model of Rao and Georgeff have been used for a number of successful applications. However, it is often difficult to learn how to apply such systems, due to the complexity of both the semantics of the system and the computational model. In addition, there is a gap between the semantics and the concepts that are presented to the programmer. In this paper we address these issues by re-casting the foundations of such systems into a logic programming framework. In particular we show how the integration of backward- and forward-chaining techniques for linear logic provides a natural starting point for this investigation. We discuss how the integrated system provides for the interaction between the proactive and reactive parts of the system, and we discuss several aspects of this interaction. In particular, one perhaps surprising outcome is that goals and plans may be thought of as declarative and procedural aspects of the same concept. We also discuss the language design issues for such a system, and particularly the way in which the potential choices for rule evaluation in a forward-chaining manner is crucial to the behaviour of the system.

Abstract. Agent systems based on the Belief, Desire and Intention model of Rao and Georgeff have been used for a number of successful applications. However, it is often difficult to learn how to apply such systems, due to the complexity of both the semantics of the system and the computational model. In addition, there is a gap between the semantics and the concepts that are presented to the programmer. One way to bridge this gap is to re-cast the foundations of such systems into a logic programming framework. In particular, the integration of backward- and forward-chaining techniques for linear logic provides a natural starting point for this investigation. In this paper we discuss the language design issues for such a system, and particularly the way in which the potential choices for rule evaluation in a forward-chaining manner is crucial to the behaviour of the system. 1 Introduction An increasingly popular programming paradigm is that of agent-oriented pro-gramming. This paradigm, often described as a natural successor to objectoriented programming [18], is highly suited for applications which are embeddedin complex dynamic environments, and is based on human concepts, such as beliefs, goals and plans. This allows a natural specification of sophisticated soft-ware systems in terms that are similar to human understanding, thus permitting programmers to concentrate on the critical properties of the application ratherthan getting absorbed in the intricate detail of a complicated environment. Agent technology has been used in areas for applications such as air traffic control, au-tomated manufacturing, and maintenance tasks on the space shuttle [19].

versatile multi-agent framework designed for Distributed Information Management tasks. SoFAR embraces the notion of proactivity as the opportunistic reuse of the services provided by other agents, and provides the means to enable agents to locate suitable service providers. The contribution of SoFAR is to combine ideas from the distributed computing community with the performative-based communications used in other agent systems: communications in SoFAR are based on the startpoint/endpoint paradigm, a powerful abstraction that can be mapped onto multiple communication layers. SoFAR also adopts an XML-based declarative approach for specifying ontologies and agents, providing a clear separation with their implementation. We explain the rationale behind our design decisions; we describe two distributed information management applications and we recount their design and operations. 1

The Australian Bureau of Meteorology is the national weather service of Australia. It has a strong need for complex and evolving systems for managing its weather forecasting, monitoring and alerts and is currently updating and reviewing software and processes to this end. The rapidly growing area of intelligent agent technology is an excellent candidate for the kind of distributed, complex and open system that is required. However in order for intelligent agents to be successfully used in this kind of system, there are some fundamental questions that must be addressed, such as how agents will find and use newly added services and how services will communicate with each other, given that they are developed independently.

For the purposes of managing an urban traffic system, a hierarchical multiagent system that consists of several locally operating agents each representing an intersection of a traffic system is proposed. Local Traffic Agents (LTAs) are concerned with the optimal performance of their assigned intersection; however, the resulting traffic light patterns may result in the failure of the system when examined at a global level. Therefore, supervision is required and achieved with the use of a Coordinator Traffic Agent (CTA). A CTA provides a means by which the optimal local light pattern can be compared against the global concerns. The pattern can then be slightly modified to accommodate the global environment, while maintaining the local concerns of the intersection. Functionality of the proposed system is examined using two traffic scenarios: traffic accident and morning rush hour. For both scenarios, the proposed multiagent system efficiently managed the gradual congestion of the traffic. As one roadway becomes more congested, the duration of the traffic lights of neighboring intersections leading towards the congested area are reduced by the CTA. If this reduction to the incoming traffic is insufficient, and the roadway continues to reach a congested state, then the LTA attempts to divert traffic using alternative directions. 1

Intelligent agents and multi-agent systems are increasingly recognized as an innovative approach for analyzing, designing and implementing complex, heterogeneous and distributed software applications. The agent-based view offers a powerful and high level conceptualization that software engineers can exploit to considerably improve the way in which software is realized. Agent-based software engineering is a recent and very interesting research area. Due to its novelty, there is still no evidence of well-established practices for the development of agent-based applications and thus experimentation in this direction is very important. This dissertation

Intelligent behavior is the selection of actions based on knowledge. The design of the Fuzzy Adaptive Survivability Tool (FAST) agents and their intelligent behavior is explained. A FAST agent uses Belief-Desire-Intention (BDI) logic as the reasoning framework to decide on desirable response plans. These decisions are both context-sensitive to take into account the changes in the network status and costsensitive to avoid the risk of collateral damage. A realworld scenario, which shows how the FAST agents choose desirable responses to mitigate scanning worm traffic, is also presented. 1.