Ontology-services agent to help in the structural and semantic heterogeneity

In the Virtual Enterprises (VE) environment, interactions between distributed heterogeneous computing entities representing different enterprises, people and resources, take place. These interactions, in order to be both syntactic and semantic compatible, need to follow appropriate standards (ontologies) well understood by all the participants. Even for each domain ontology, people may store their data in different structures and use different terms to represent the same concept. This paper focuses on an effort to create an Ontology-Services Agent to monitor the communication acts taking place in a Multi-agent System. The Ontology-Services Agent provides help in solving the Structural and Semantic Heterogeneity problem, enabling appropriate conversations and making it possible meaningful agreements between agents representing different enterprises and resources in a VE environment

AGENT-BASED NEGOTIATION PLATFORM IN COLLABORATIVE NETWORKED ENVIRONMENT

This paper proposes an agent-based platform to model and support parallel and concurrent negotiations among organizations acting in the same industrial market. The underlying complexity is to model the dynamic environment where multi-attribute and multi-participant negotiations are racing over a set of heterogeneous resources. The metaphor Interaction Abstract Machines (IAMs) is used to model the parallelism and the non-deterministic aspects of the negotiation processes that occur in Collaborative Networked Environment

Ontology-based services for agents interoperability

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2006. Faculdade de Engenharia. Universidade do Port

A formal foundation for ontology alignment interaction models

Ontology alignment foundations are hard to find in the literature. The abstract nature of the topic and the diverse means of practice makes it difficult to capture it in a universal formal foundation. We argue that such a lack of formality hinders further development and convergence of practices, and in particular, prevents us from achieving greater levels of automation. In this article we present a formal foundation for ontology alignment that is based on interaction models between heterogeneous agents on the Semantic Web. We use the mathematical notion of information flow in a distributed system to ground our three hypotheses of enabling semantic interoperability and we use a motivating example throughout the article: how to progressively align two ontologies of research quality assessment through meaning coordination. We conclude the article with the presentation---in an executable specification language---of such an ontology-alignment interaction model

An ontology-based spatial group decision support system for site selection application

This paper presents a new ontology-based multicriteria spatial group decision support system (GDSS) dedicated to site selection problems. Site selection is one of the most complex problems in the construction of a new building. It presents a crucial problem in terms of selecting the appropriate site among a group of decision makers with multiple alternatives (sites); in addition, the site must satisfy several criteria. To deal with this, the present paper introduces an ontology based multicriteria analysis method to solve semantic heterogeneity in vocabulary used by participants in spatial group decision support systems. The advantages of using ontology in GDSS are many: i) it enables the integration of heterogeneous sources of data available on the web and ii) it enables to facilitate meaning and sharing of data used in GDSS by participants. In order to facilitate cooperation and collaboration between participants in GDSS, our work aims to apply ontology at the model's structuration phase. The proposed system has been successfully implemented and exploited for a personalized environment

Agents in Bioinformatics

The scope of the Technical Forum Group (TFG) on Agents in Bioinformatics (BIOAGENTS) was to inspire collaboration between the agent and bioinformatics communities with the aim of creating an opportunity to propose a different (agent-based) approach to the development of computational frameworks both for data analysis in bioinformatics and for system modelling in computational biology. During the day, the participants examined the future of research on agents in bioinformatics primarily through 12 invited talks selected to cover the most relevant topics. From the discussions, it became clear that there are many perspectives to the field, ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages for use by information agents, and to the use of Grid agents, each of which requires further exploration. The interactions between participants encouraged the development of applications that describe a way of creating agent-based simulation models of biological systems, starting from an hypothesis and inferring new knowledge (or relations) by mining and analysing the huge amount of public biological data. In this report we summarise and reflect on the presentations and discussions

Autonomous Agents for Business Process Management

Traditional approaches to managing business processes are often inadequate for large-scale organisation-wide, dynamic settings. However, since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore, a new approach is needed. To this end, we describe the motivation, conceptualization, design, and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our system to a real-world problem faced by British Telecom