Many open networks, distributed computing systems, and infrastructure management systems face a common problem: how to distribute a collectivised set of resources amongst a set of autonomous agents of heterogenous provenance. One approach is for the agents themselves to self-organise the allocation of resources with respect to a set of agreed conventional rules; but given an allocation scheme which maps resources to those agents and a set of rules for determining that allocation scheme, some natural questions arise—Is this allocation fair? (...) Is the allocation method effective? Is it efficient? Are the decision makers accountable? In this paper, we argue that some answers to these questions can be found in the formal characterisation of different aspects of ‘justice’ and that these different aspects need a principled operationalisation as policies for system management. We present a formal model and some experimental results, concluding that the different aspects are all inter-connected and that what is required is a comprehensive research programme in computational justice. (shrink)

Probabilistic argumentation and neuro-argumentative systems offer new computational perspectives for the theory and applications of argumentation, but their principled construction involves two entangled problems. On the one hand, probabilistic argumentation aims at combining the quantitative uncertainty addressed by probability theory with the qualitative uncertainty of argumentation, but probabilistic dependences amongst arguments as well as learning are usually neglected. On the other hand, neuro-argumentative systems offer the opportunity to couple the computational advantages of learning and massive parallel computation from neural networks (...) with argumentative reasoning and explanatory abilities, but the relation of probabilistic argumentation frameworks with these systems has been ignored so far. Towards the construction of neuro-argumentative systems based on probabilistic argumentation, we associate a model of abstract argumentation and the graphical model of Boltzmann machines in order to (i... (shrink)

Cloud computing deals with voluminous heterogeneous data, and there is a need to effectively distribute the load across clusters of nodes to achieve optimal performance in terms of resource usage, throughput, response time, reliability, fault tolerance, and so on. The swarm intelligence methodologies use artificial intelligence to solve computationally challenging problems like load balancing, scheduling, and resource allocation at finite time intervals. In literature, sufficient works are being carried out to address load balancing problem in the cloud using traditional swarm (...) intelligence techniques like ant colony optimization, particle swarm optimization, cuckoo search, bat optimization, and so on. But the traditional swarm intelligence techniques have issues with respect to convergence rate, arriving at the global optimum solution, complexity in implementation and scalability, which limits the applicability of such techniques in cloud domain. In this paper, we look into performance modeling aspects of some of the recent competitive swarm artificial intelligence based techniques like the whale, spider, dragonfly, and raven which are used for load balancing in the cloud. The results and analysis are presented over performance metrics such as total execution time, response time, resource utilization rate, and throughput achieved, and it is found that the performance of the raven roosting algorithm is high compared to other techniques. (shrink)

A thematic priority of the European Union’s Framework V research and development programme was the creation of a user-friendly information society which met the needs of citizens and enterprises. In practice, though, for example in the case of on-line digital music, the needs of citizens and enterprises may be in conflict. This paper proposes to leverage the appearance of ‘intelligence’ in the platform layer of a layered communications architecture to avoid such conflicts in similar applications in the future. The key (...) idea is that if the intelligence is encapsulated in an agent, then the agents should be organized as a society, and then the rules of the society can be used to ensure ‘responsible’ behaviour. We discuss how an agent society can be used to regulate behaviour in future information trading scenarios, and conclude that this approach offers a ‘third way’ which can satisfy the (reasonable) needs of both citizens and enterprises in the user-friendly information society. (shrink)

It is now more than ten years since the EU FET project ALFEBIITE finished, during which its researchers made original and distinctive contributions to (inter alia) formal models of trust, model-checking, and action logics. ALFEBIITE was also a highly inter-disciplinary project, with partners from computer science, philosophy, cognitive science and law. In this paper, we reflect on the interaction between computer scientists and information and IT lawyers on the idea of the ‘open agent society’. This inspired a programme of research (...) whose investigation into conceptual challenges has carried it from the logical specification of agent societies and dynamic norm-governed systems to self-organising electronic institutions, while developing several technologies for agent-based modelling and complex event recognition. The outcomes of this inter-disciplinary collaboration have also influenced current research into using the open agent society as a platform for socio-technical systems, and other collective adaptive systems. We present a number of research challenges, including the ideas of computational justice and polycentric governance, and explore a number of ethical, legal and social implications. We contend that, in order to address these issues and challenges, the continued inter-disciplinary collaboration between computer science and IT lawyers is critical. (shrink)

People’s decisions and actions are informed, influenced, and constrained by socially constructed social arrangements. Usually, these social arrangements are pre-determined, and people joining institutions or organizations may have, at least initially, little control or influence over them. Occasionally, however, but increasingly commonly in the transition to the “Digital Society,” people have an opportunity to self-determine their social arrangements “from scratch.” The issues then are: how do people gain experience in such founding processes, experiment safely with alternative social arrangements, and gain (...) expertise so that they can participate meaningfully, for example in consultation events. In this research paper, we address these issues by presenting a framework for “computer-supported social arrangements” tools which would enable people to specify, learn, apply, evaluate, and innovate social arrangements. This would contribute to empowering people and communities with the necessary experience, experimentation, and expertise for effective and sustainable self-determination of their own social arrangements. (shrink)

A Prolog implementation of a new theorem-prover for first-order classical logic is described. The prover is based on the calculus KE and the rules used for analysing quantifiers in free variable semantic tableaux. A formal specification of the rules used in the implementation is described, for which soundness and completeness is straightforwardly verified. The prover has been tested on the first 47 problems of the Pelletier set, and its performance compared with a state of the art semantic tableaux theorem-prover. It (...) has also been applied to model building in a prototype system for logical animation, a technique for symbolic execution which can be used for validation. The interest of these experiments is that they demonstrate the value of certain “characteristics” of the KE calculus, such as the significant space-saving in theorem-proving, the mutual inconsistency of open branches in KE trees, and the relation of the KE rules to “traditional” forms of reasoning. (shrink)