The concept of an agent is increasingly used in contemporary software applications, particularly those involving the Internet, autonomous systems, or cooperation. However, with dependability and safety in mind, it is vital that the mechanisms for representing and implementing agents are clear and consistent. Hence there has been a strong research effort directed at using formal logic as the basis for agent descriptions and agent implementation. Such a logical basis not only presents the clarity and consistency required but also allows for important techniques such as logical verification to be applied. We present a roadmap of research into the use of computational logic in agent-based systems and survey much of the recent work in these areas. Even though, with such a rapidly changing field, it is impossible to cover every development, we aim to give the reader sufficient background to understand the current research problems and potential future developments in this maturing area.

This paper presents the computational logic foundations of a model of agency called the KGP (Knowledge, Goals and Plan) model. This model allows the specification of heterogeneous agents that can interact with each other, and can exhibit both proactive and reactive behaviour allowing them to function in dynamic environments by adjusting their goals and plans when changes happen in such environments. KGP provides a highly modular agent architecture that integrates a collection of reasoning and physical capabilities, synthesised within transitions that update the agent’s state in response to reasoning, sensing and acting. Transitions are orchestrated by cycle theories that specify the order in which transitions are executed while taking into account the dynamic context and agent preferences, as well as selection operators for providing inputs to transitions. 1.

“Agents and Artifacts ” (A&A) and CARTAGO are becoming increasingly popular as, respectively, a general-purpose programming model and a related infrastructure for developing shared computational environments in agent-based software systems. However, so far there has been no work on developing multiagent systems (MAS) where agents implemented and deployed in different agent-programming platforms can interact as part of the same MAS with a shared environment. Due to the generality of CARTAGO environments and its Java-based implementation, we have successfully implemented an open multi-agent system where heterogeneous agents developed with different platforms—namely Jason, 2APL as BDI-based approaches and simpA as an activityoriented approach rather than BDI-based—work together in

Reasoning about Risk in Agent’s Deliberation Process: a Jadex Implementation Autonomous agents and multi-agent systems have been proved to be useful in several safety-critical applications. However, in current agent architectures (particularly BDI architectures) the deliberation process does not include any form of risk analysis. In this paper, we propose guidelines to implement Tropos Goal-Risk reasoning. Our proposal aims at introducing risk reasoning in the deliberation process of a BDI agent so that the overall set of possible plans is evaluated with respect to risk. When the level of risk results too high, agents can consider and introduce additional plans, called treatments, that produce an overall reduction of the risk. Side effects of treatments are also considered as part of the model. To make the discussion more concrete, we illustrate the proposal with a case study on the Unmanned Aerial Vehicle agent. 1

Abstract. This chapter tackles the relation between declarative languages and multi-agent systems by following the dictates of the five Ws (and one H) that characterize investigations. The aim is to present this research field, which has a long-term tradition, and discuss about its future. The first question to answer is “What? What are declarative agents and multi-agent systems?”. Therefore, we will introduce the history of declarative agent systems up to the state of the art by answering the question “When? When did research on them begin?”. We will, then, move to the question “Where? Where can it take place?”: in which kind of real applications and for which kind of problems declarative agents and MAS have already proven useful? Connected to where is “Why? Why should it happen?”. We will discuss the benefits of adopting the abstractions offered by declarative approaches for developing communication, interaction, cooperation mechanisms. We will compare with other technologies, mainly service-based and object-oriented ones. “Who? Who can be involved?”: in order to exploit this kind of technology what sort of background does a specialist have to acquire?

Abstract—Agents and Multi-Agent Systems are recognized in the literature as a suitable paradigm for engineering SOA and Web Service systems: however few works explore how to exploit agent programming languages – in particular those based on a strong notion of agency, such as BDI ones – for concretely developing such a kind of systems. In this paper we discuss a general-purpose programming model and a related platform for developing SOA/WS applications exploiting BDI agent technologies. In particular, in order to enable agents to exploit and manage web service technologies in a suitable functional fashion, we investigate the use of Jason agents – based on AgentSpeak(L) programming language – integrated with artifactbased environments – based on CArtAgO-WS framework. I.

Semantic Web technologies are part of multi-agent engineering, especially regarding knowledge base support. Recent advances in the field of logic for the semantic web enable a new range of applications. Among them, programming agents based on semantic rules is a promising field. In this paper we present an semantic agent model that allows SWRL programming of agents. Our approach based on the extended finite state machine concept results in a three layers architecture. We detail the architecture, the syntax of the rules, the agent interpreter cycle and present a prototype validating the concept. 1. Introduction and

Augmenting BDI with relevance

Abstract Systems of autonomous and self-interested agents interacting to achieve individual and collective goals may exhibit undesirable or unexpected properties if left unconstrained. Using deontic concepts of obligations, permissions and prohibitions to describe, what must, may and should not be done, norms have been widely proposed as a means of defining and enforcing societal constraints. Recent efforts to provide norm-enabled agent architectures that limit plan choices suffer from interfering with an agent’s reasoning process, and thus limit autonomy more than is required by the norms alone. In response, in this paper we describe an extension of the BDI architecture which enables normative reasoning, providing agents with a means to choose and customise plans (and their constituent actions), so as to ensure compliance with norms. 1

Abstract—The design and development of a large Multi Agent System (MAS) is a complex and difficult activity where a proper modeling notation may offer a significant contribution to the formulation of the best solution. The support provided by a specific CASE tool can significantly contribute to make the chosen approach technically valid and it is also a fundamental element of a feasible development strategy. The present work reports a UML profile and the related graphical notation for describing a MAS based on the Jason metamodel. Moreover a specific CASE tool has been developed for supporting MASs design and automatic code generation. The proposed notation is shown in details using a classical example from the Jason tutorial (domestic robot). Keywords-Jason; Multi-agent system; CASE tool I.