Beliefs and Conflicts in a Real World Multiagent System

In a real world multiagent system, where the agents are faced with partial, incomplete and intrinsically dynamic knowledge, conflicts are inevitable. Frequently, different agents have goals or beliefs that cannot hold simultaneously. Conflict resolution methodologies have to be adopted to overcome such undesirable occurrences. In this paper we investigate the application of distributed belief revision techniques as the support for conflict resolution in the analysis of the validity of the candidate beams to be produced in the CERN particle accelerators. This CERN multiagent system contains a higher hierarchy agent, the Specialist agent, which makes use of meta-knowledge (on how the conflicting beliefs have been produced by the other agents) in order to detect which beliefs should be abandoned. Upon solving a conflict, the Specialist instructs the involved agents to revise their beliefs accordingly. Conflicts in the problem domain are mapped into conflicting beliefs of the distributed belief revision system, where they can be handled by proven formal methods. This technique builds on well established concepts and combines them in a new way to solve important problems. We find this approach generally applicable in several domains

Improving Assumption based Distributed Belief Revision

Belief revision is a critical issue in real world DAI applications. A Multi-Agent System not only has to cope with the intrinsic incompleteness and the constant change of the available knowledge (as in the case of its stand alone counterparts), but also has to deal with possible conflicts between the agents’ perspectives. Each semi-autonomous agent, designed as a combination of a problem solver – assumption based truth maintenance system (ATMS), was enriched with improved capabilities: a distributed context management facility allowing the user to dynamically focus on the more pertinent contexts, and a distributed belief revision algorithm with two levels of consistency. This work contributions include: (i) a concise representation of the shared external facts; (ii) a simple and innovative methodology to achieve distributed context management; and (iii) a reduced inter-agent data exchange format. The different levels of consistency adopted were based on the relevance of the data under consideration: higher relevance data (detected inconsistencies) was granted global consistency while less relevant data (system facts) was assigned local consistency. These abilities are fully supported by the ATMS standard functionalities

Distributed Belief Revision and Environmental Decision Support

This article discusses the development of an Intelligent Distributed Environmental Decision Support System, built upon the association of a Multi-agent Belief Revision System with a Geographical Information System (GIS). The inherent multidisciplinary features of the involved expertises in the field of environmental management, the need to define clear policies that allow the synthesis of divergent perspectives, its systematic application, and the reduction of the costs and time that result from this integration, are the main reasons that motivate the proposal of this project. This paper is organised in two parts: in the first part we present and discuss the developed - Distributed Belief Revision Test-bed - DiBeRT; in the second part we analyse its application to the environmental decision support domain, with special emphasis on the interface with a GIS

Environmental Decision Support: a Distributed Artificial Intelligence Approach

Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations

A proposal for media component brokerage

This paper describes how MPEG-4 object based video (obv) can be used to allow selected objects to be inserted into the play-out stream to a specific user based on a profile derived for that user. The application scenario described here is for personalized product placement, and considers the value of this application in the current and evolving commercial media distribution market given the huge emphasis media distributors are currently placing on targeted advertising. This level of application of video content requires a sophisticated content description and metadata system (e.g., MPEG-7). The scenario considers the requirement for global libraries to provide the objects to be inserted into the streams. The paper then considers the commercial trading of objects between the libraries, video service providers, advertising agencies and other parties involved in the service. Consequently a brokerage of video objects is proposed based on negotiation and trading using intelligent agents representing the various parties. The proposed Media Brokerage Platform is a multi-agent system structured in two layers. In the top layer, there is a collection of coarse grain agents representing the real world players – the providers and deliverers of media contents and the market regulator profiler – and, in the bottom layer, there is a set of finer grain agents constituting the marketplace – the delegate agents and the market agent. For knowledge representation (domain, strategic and negotiation protocols) we propose a Semantic Web approach based on ontologies. The media components contents should be represented in MPEG-7 and the metadata describing the objects to be traded should follow a specific ontology. The top layer content providers and deliverers are modelled by intelligent autonomous agents that express their will to transact – buy or sell – media components by registering at a service registry. The market regulator profiler creates, according to the selected profile, a market agent, which, in turn, checks the service registry for potential trading partners for a given component and invites them for the marketplace. The subsequent negotiation and actual transaction is performed by delegate agents in accordance with their profiles and the predefined rules of the market

EGNOS based virtual reference stations

We propose the use of the European Geostationary Navigation Overlay Service (EGNOS) data - real time on line data provided by SISNeT - to develop Virtual Reference Stations and, thus, increase the quality of the Position, Velocity an Time (PVT) solution of receivers unable to interface directly with EGNOS. A Virtual Reference Station (VRS) is a concept where the existence of a differential reference station located near a mobile rover is simulated by software in order to increase the accuracy of the PVT solution of the mobile GNSS receiver

Belief Revision in Multi-Agent Systems

The ability to respond sensibly to changing and conflicting beliefs is an integral part of intelligent agency. To this end, we outline the design and implementation of a Distributed Assumption-based Truth Maintenance System (DATMS) appropriate for controlling cooperative problem solving in a dynamic real world multi-agent community. Our DATMS works on the principle of local coherence which means that different agents can have different perspectives on the same fact provided that these stances are appropriately justified. The belief revision algorithm is presented, the meta-level code needed to ensure that all system-wide queries can be uniquely answered is described, and the DATMS’ implementation in a general purpose multi-agent shell is discussed

Beliefs and Conflicts in a Real World Multi-Agent System

In a real world multiagent system, where the agents are faced with partial, incomplete and intrinsically dynamic knowledge, conflicts are inevitable. Frequently, different agents have goals or beliefs that cannot hold simultaneously. Conflict resolution methodologies have to be adopted to overcome such undesirable occurrences. In this paper we investigate the application of distributed belief revision techniques as the support for conflict resolution in the analysis of the validity of the candidate beams to be produced in the CERN particle accelerators. This CERN multiagent system contains a higher hierarchy agent, the Specialist agent, which makes use of meta-knowledge (on how the con- flicting beliefs have been produced by the other agents) in order to detect which beliefs should be abandoned. Upon solving a conflict, the Specialist instructs the involved agents to revise their beliefs accordingly. Conflicts in the problem domain are mapped into conflicting beliefs of the distributed belief revision system, where they can be handled by proven formal methods. This technique builds on well established concepts and combines them in a new way to solve important problems. We find this approach generally applicable in several domains

RemoteLabs Platform

This paper reports on a first step towards the implementation of a framework for remote experimentation of electric machines ? the RemoteLabs platform. This project was focused on the development of two main modules: the user Web-based and the electric machines interfaces. The Web application provides the user with a front-end and interacts with the back-end ? the user and experiment persistent data. The electric machines interface is implemented as a distributed client server application where the clients, launched by the Web application, interact with the server modules located in platforms physically connected the electric machines drives. Users can register and authenticate, schedule, specify and run experiments and obtain results in the form of CSV, XML and PDF files. These functionalities were successfully tested with real data, but still without including the electric machines. This inclusion is part of another project scheduled to start soon

B2B platform for media content personalisation

This paper proposes a novel business model to support media content personalisation: an agent-based business-to-business (B2B) brokerage platform for media content producer and distributor businesses. Distributors aim to provide viewers with a personalised content experience and producers wish to en-sure that their media objects are watched by as many targeted viewers as possible. In this scenario viewers and media objects (main programmes and candidate objects for insertion) have profiles and, in the case of main programme objects, are annotated with placeholders representing personalisation opportunities, i.e., locations for insertion of personalised media objects. The MultiMedia Brokerage (MMB) platform is a multiagent multilayered brokerage composed by agents that act as sellers and buyers of viewer stream timeslots and/or media objects on behalf of the registered businesses. These agents engage in negotiations to select the media objects that best match the current programme and viewer profiles