Intelligent ethics.

This paper discusses the impact of envisaged intelligent applications on the lives of the individuals who may be using them, and investigates the ethical implications of autonomous decision-making that is beyond the control of the user. In an increasingly networked world we look beyond the individual to a social picture of distributed multi-agent interaction, and in particular at the concepts of rules and negotiation between these virtual social agents. We suggest that the use of such agents in a wider social context requires an element of ethical thinking to take place at the grass roots level – that is, with the designers and developers of such systems

Models of Interaction as a Grounding for Peer to Peer Knowledge Sharing

Most current attempts to achieve reliable knowledge sharing on a large scale have relied on pre-engineering of content and supply services. This, like traditional knowledge engineering, does not by itself scale to large, open, peer to peer systems because the cost of being precise about the absolute semantics of services and their knowledge rises rapidly as more services participate. We describe how to break out of this deadlock by focusing on semantics related to interaction and using this to avoid dependency on a priori semantic agreement; instead making semantic commitments incrementally at run time. Our method is based on interaction models that are mobile in the sense that they may be transferred to other components, this being a mechanism for service composition and for coalition formation. By shifting the emphasis to interaction (the details of which may be hidden from users) we can obtain knowledge sharing of sufficient quality for sustainable communities of practice without the barrier of complex meta-data provision prior to community formation

Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

Distributed on-line safety monitor based on safety assessment model and multi-agent system

On-line safety monitoring, i.e. the tasks of fault detection and diagnosis, alarm annunciation, and fault controlling, is essential in the operational phase of critical systems. Over the last 30 years, considerable work in this area has resulted in approaches that exploit models of the normal operational behaviour and failure of a system. Typically, these models incorporate on-line knowledge of the monitored system and enable qualitative and quantitative reasoning about the symptoms, causes and possible effects of faults. Recently, monitors that exploit knowledge derived from the application of off-line safety assessment techniques have been proposed. The motivation for that work has been the observation that, in current practice, vast amounts of knowledge derived from off-line safety assessments cease to be useful following the certification and deployment of a system. The concept is potentially very useful. However, the monitors that have been proposed so far are limited in their potential because they are monolithic and centralised, and therefore, have limited applicability in systems that have a distributed nature and incorporate large numbers of components that interact collaboratively in dynamic cooperative structures. On the other hand, recent work on multi-agent systems shows that the distributed reasoning paradigm could cope with the nature of such systems. This thesis proposes a distributed on-line safety monitor which combines the benefits of using knowledge derived from off-line safety assessments with the benefits of the distributed reasoning of the multi-agent system. The monitor consists of a multi-agent system incorporating a number of Belief-Desire-Intention (BDI) agents which operate on a distributed monitoring model that contains reference knowledge derived from off-line safety assessments. Guided by the monitoring model, agents are hierarchically deployed to observe the operational conditions across various levels of the hierarchy of the monitored system and work collaboratively to integrate and deliver safety monitoring tasks. These tasks include detection of parameter deviations, diagnosis of underlying causes, alarm annunciation and application of fault corrective measures. In order to avoid alarm avalanches and latent misleading alarms, the monitor optimises alarm annunciation by suppressing unimportant and false alarms, filtering spurious sensory measurements and incorporating helpful alarm information that is announced at the correct time. The thesis discusses the relevant literature, describes the structure and algorithms of the proposed monitor, and through experiments, it shows the benefits of the monitor which range from increasing the composability, extensibility and flexibility of on-line safety monitoring to ultimately developing an effective and cost-effective monitor. The approach is evaluated in two case studies and in the light of the results the thesis discusses and concludes both limitations and relative merits compared to earlier safety monitoring concepts