From SMART to agent systems development

In order for agent-oriented software engineering to prove effective it must use principled notions of agents and enabling specification and reasoning, while still considering routes to practical implementation. This paper deals with the issue of individual agent specification and construction, departing from the conceptual basis provided by the SMART agent framework. SMART offers a descriptive specification of an agent architecture but omits consideration of issues relating to construction and control. In response, we introduce two new views to complement SMART: a behavioural specification and a structural specification which, together, determine the components that make up an agent, and how they operate. In this way, we move from abstract agent system specification to practical implementation. These three aspects are combined to create an agent construction model, actSMART, which is then used to define the AgentSpeak(L) architecture in order to illustrate the application of actSMART

Computational Systems for Music Improvisation

Computational music systems that afford improvised creative interaction in real time are often designed for a specific improviser and performance style. As such the field is diverse, fragmented and lacks a coherent framework. Through analysis of examples in the field we identify key areas of concern in the design of new systems, which we use as categories in the construction of a taxonomy. From our broad overview of the field we select significant examples to analyse in greater depth. This analysis serves to derive principles that may aid designers scaffold their work on existing innovation. We explore successful evaluation techniques from other fields and describe how they may be applied to iterative design processes for improvisational systems. We hope that by developing a more coherent design and evaluation process, we can support the next generation of improvisational music systems

A normative framework for agent-based systems

One of the key issues in the computational representation of open societies relates to the introduction of norms that help to cope with the heterogeneity, the au- tonomy and the diversity of interests among their members. Research regarding this issue presents two omissions. One is the lack of a canonical model of norms that facil- itates their implementation, and that allows us to describe the processes of reasoning about norms. The other refers to considering, in the model of normative multi-agent systems, the perspective of individual agents and what they might need to effectively reason about the society in which they participate. Both are the concerns of this paper, and the main objective is to present a formal normative framework for agent-based systems that facilitates their implementation

A conceptual framework for agent definition and development

The use of agents of many different kinds in a variety of fields of computer science and artificial intelligence is increasing rapidly and is due, in part, to their wide applicability. The richness of the agent metaphor that leads to many different uses of the term is, however, both a strength and a weakness: its strength lies in the fact that it can be applied in very many different ways in many situations for different purposes; the weakness is that the term agent is now used so frequently that there is no commonly accepted notion of what it is that constitutes an agent. This paper addresses this issue by applying formal methods to provide a defining framework for agent systems. The Z specification language is used to provide an accessible and unified formal account of agent systems, allowing us to escape from the terminological chaos that surrounds agents. In particular, the framework precisely and unambiguously provides meanings for common concepts and terms, enables alternative models of particular classes of system to be described within it, and provides a foundation for subsequent development of increasingly more refined concepts.

Motivated behaviour for goal adoption

Abstract. Social behaviour arises as a result of individual agents cooperating with each other so as to exploit the resources available in a rich and dynamic multi-agent domain. If agents are to make use of others to help them in their tasks, such social behaviour is critical. Underlying this cooperation is the transfer or adoption of goals from one agent to another, a subtle and complex process that depends on the nature of the agents involved. In this paper we analyse this process by building upon a hierarchy previously constructed to define objects, agents and autonomous agents. We describe the motivated self-generation of goals that defines agent autonomy and the adoption of goals between agents that enables social behaviour. Then we consider three classes of goal adoption by objects, agents and autonomous agents. The first of these is merely a question of instantiation, the second requires an understanding of the relationship of the agent to others that are engaging it, and the third amounts to a question of negotiation or persuasion.

Combining cauchy and characteristic codes. V. cauchy-characteristic matching for a spherical spacetime containing a perfect fluid

This paper is part of a long term program to develop CCM (combined Cauchy and characteristic) codes as investigative tools in numerical relativity. The approach has two distinct features: (i) it dispenses with an outer boundary condition and replaces this with matching conditions at an interface between the Cauchy and characteristic regions, and (ii) by employing a compactified coordinate, it proves possible to generate global solutions. In this paper it is shown that CCM can be used effectively to model a spherically symmetric perfect fluid. A particular advantage of CCM in avoiding arbitrary mass inflow-outflow boundary conditions is pointed out. Results are presented which include fluid distributions which form black holes and those which give rise to mass outflow.<br/

Explainable Computational Creativity

Human collaboration with systems within the Computational Creativity (CC) field is often restricted to shallow interactions, where the creative processes, of systems and humans alike, are carried out in isolation, without any (or little) intervention from the user, and without any discussion about how the unfolding decisions are taking place. Fruitful co-creation requires a sustained ongoing interaction that can include discussions of ideas, comparisons to previous/other works, incremental improvements and revisions, etc. For these interactions, communication is an intrinsic factor. This means giving a voice to CC systems and enabling two-way communication channels between them and their users so that they can: explain their processes and decisions, support their ideas so that these are given serious consideration by their creative collaborators, and learn from these discussions to further improve their creative processes. For this, we propose a set of design principles for CC systems that aim at supporting greater cocreation and collaboration with their human collaborators