Novel Negotiation protocol to support CDM process in a layered ATM System

In the SESAR Step 2 concept of operations a RBT is available and seen by all making it possible to conceive a different operating method than the current ATM system based on Collaborative Decisions Making processes. Currently there is a need to describe in more detail the mechanisms by which actors (ATC, Network Management, Flight Crew, airports and Airline Operation Centre) will negotiate revisions to the RBT. This paper introduces a negotiation model, which uses constraint based programing applied to a mediator to facilitate negotiation process in a SWIM enabled environment. Three processes for modelling the negotiation process are explained as well a preliminary reasoning agent algorithm modelled with constraint satisfaction problem is presented. Computational capability of the model is evaluated in the conclusion

Using evidence combination for transformer defect diagnosis

This paper describes a number of methods of evidence combination, and their applicability to the domain of transformer defect diagnosis. It explains how evidence combination fits into an on-line and implemented agent-based condition monitoring system, and the benefits of giving selected agents reflective abilities. Reflection has not previously been deployed in an industrial setting, and theoretical work has been in domains other than power engineering. This paper presents the results of implementing five different methods of evidence combination, showing that reflective techniques give greater accuracy than non-reflective

Engineering Agent Systems for Decision Support

This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain

A Generic Conceptual Model for Risk Analysis in a Multi-agent Based Collaborative Design Environment

Organised by: Cranfield UniversityThis paper presents a generic conceptual model of risk evaluation in order to manage the risk through related constraints and variables under a multi-agent collaborative design environment. Initially, a hierarchy constraint network is developed to mapping constraints and variables. Then, an effective approximation technique named Risk Assessment Matrix is adopted to evaluate risk level and rank priority after probability quantification and consequence validation. Additionally, an Intelligent Data based Reasoning Methodology is expanded to deal with risk mitigation by combining inductive learning methods and reasoning consistency algorithms with feasible solution strategies. Finally, two empirical studies were conducted to validate the effectiveness and feasibility of the conceptual model.Mori Seiki – The Machine Tool Compan

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Automated post-fault diagnosis of power system disturbances

In order to automate the analysis of SCADA and digital fault recorder (DFR) data for a transmission network operator in the UK, the authors have developed an industrial strength multi-agent system entitled protection engineering diagnostic agents (PEDA). The PEDA system integrates a number of legacy intelligent systems for analyzing power system data as autonomous intelligent agents. The integration achieved through multi-agent systems technology enhances the diagnostic support offered to engineers by focusing the analysis on the most pertinent DFR data based on the results of the analysis of SCADA. Since November 2004 the PEDA system has been operating online at a UK utility. In this paper the authors focus on the underlying intelligent system techniques, i.e. rule-based expert systems, model-based reasoning and state-of-the-art multi-agent system technology, that PEDA employs and the lessons learnt through its deployment and online use

Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

On the emergent Semantic Web and overlooked issues

The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues