Vicente J. Botti

Intelligent Data Engineering and Automated Learning – IDEAL 2006

Learning and Information Processing -- Data Mining, Retrieval and Management -- Bioinformatics and Bio-inspired Models -- Agents and Hybrid Systems -- Financial Engineering -- Special Session on Nature-Inspired Date Technologies.

Holons and agents

The future of the manufacturing sector in the world will be determined by how it meets the challenges of the 21st century. Two paradigms promise to meet these challenges, multi-agent systems (MAS) and holonic system (HS). Currently, there is some misunderstanding about the relationships between these two approaches. The aim of this work is to make a study of all the characteristics of the HS and the MAS approach, in order to illustrate a comprehensive comparison of holons and agents, and, at the same time, to present a survey about the main research works in both areas.

Hybrid multi-agent architecture as a real-time problem-solving model

This paper presents a multi-agent architecture that facilitates the development of real-time multi-agent systems based on the SIMBA approach. The approach allows the integration of unbounded deliberative processes with critical real-time tasks. CBP-BDI deliberative agents collaborate with ARTIS agents in order to solve real-time problems efficiently. The proposal has been successfully tested and evaluated in a case study based on the use of mobile robots for mail delivery.

Multi-Agent System Development Based on Organizations

Organizational models have been recently used in agent theory for modeling coordination in open systems and to ensure social order in multi-agent system applications. In this paper, we propose the employment of Organization Theory for the analysis and design of multiagent systems. Thus, we first discuss the current state of the art of organization-oriented multiagent system methods, placing emphasis on their organizational features. We also review human organizational structures, and we propose several guidelines for implementing agent organizations by means of Organization Theory. Our final aim is to employ well-known human organizational structures to develop multiagent systems.

An abstract architecture for virtual organizations: The THOMAS approach

Today, the need for architectures and computational models for large-scale open multi-agent systems is considered to be a key issue for the success of agent technology in real-world scenarios. This paper analyzes the significant unsolved problems that must be taken into account in order to develop real, open multi-agent systems. It identifies requirements and related open issues, discusses how some of these requirements have been tackled by current technologies, and explains how the THOMAS architecture is able to give support to these open issues. This paper also describes the THOMAS abstract architecture and computational model for large-scale open multi-agent systems based on a service-oriented approach that specifically addresses the design of virtual organizations. An application example for the management of a travel agency system, which demonstrates the new features of the proposal, is also presented.

Engineering Holonic Manufacturing Systems

Holonic Manufacturing Systems (HMS) was first proposed as a new manufacturing paradigm at the beginning of 1990 and has subsequently received a lot of attention in academic and industrial research. The application of holonic concepts to manufacturing was initially motivated by the inadequacy of existing manufacturing systems in the following two aspects: (i) dealing with the evolution of products within an existing production facility, and (ii) maintaining a satisfactory performance outside of normal operating conditions. In spite of the large number of developments reported in Holonic Control Architectures and Holonic Control Algorithms, there is very little work reported on Methodologies for HMS. Manufacturing requirements impose significant properties on HMS making the modelling process of HMS a complex and difficult task. In this work we describe how to engineer Holonic Manufacturing Systems using a Multi-agent System method. Our approach is based on holonic systems specific requirements, and it incorporates software engineering principles in order to assist the system designers at each development stage. It implements a collaborative-engineering process for HMS, and provides clear and unambiguous analysis and design guidelines.

MAS Modeling Based on Organizations

An agent organization model is proposed based on four main concepts: organizational unit, service, environment and norm. These concepts are integrated in ANEMONA meta-models, which are extended in order to include all entities needed for describing the structure, functionality, dynamic, normalization and environment of an organization.

Agent-based virtual organization architecture

The purpose of this paper is to present the applicability of THOMAS, an architecture specially designed to model agent-based virtual organizations, in the development of a multiagent system for managing and planning routes for clients in a mall. In order to build virtual organizations, THOMAS offers mechanisms to take into account their structure, behaviour, dynamic, norms and environment. Moreover, one of the primary characteristics of the THOMAS architecture is the use of agents with reasoning and planning capabilities. These agents can perform a dynamic reorganization when they detect changes in the environment. The proposed architecture is composed of a set of related modules that are appropriate for developing systems in highly volatile environments similar to the one presented in this study. This paper presents THOMAS as well as the results obtained after having applied the system to a case study.

Application of Artificial Neural Networks to Combinatorial Catalysis: Modeling and Predicting ODHE Catalysts

This paper shows how artificial neural networks are useful for modeling catalytic data from combinatorial catalysis and for predicting new potential catalyst compositions for the oxidative dehydrogenation of ethane (ODHE). The training and testing sets of data used for the neural network studies were obtained by means of a combinatorial approach search, which employs an evolutionary optimization strategy. Input and output variables of the neural network include the molar composition of thirteen different elements presented in the catalyst and five catalytic performances (C2H6 and O2 conversion, C2H4 yield, and C2H4, CO2, and CO selectivity). The fitting results indicate that neural networks can be useful in high-dimensional data management within combinatorial catalysis search procedures, since neural networks allow the ab initio evaluation of the reactivity of multicomponent catalysts.

Modelling Agents in Hard Real-Time Environments

Over the last few years more complex techniques have been used to develop hard real-time systems, and the multi-agent system paradigm seems to be an appropriate approach to be applied in this area. The temporal restrictions of these systems made necessary to build agents architectures that satisfy these restrictions. A formal Agent architecture to model hard-real time systems is proposed in this paper. A prototype that follows this agent architecture and works in a hard real-time environment has been implemented. Finally, a study case is described to show the design agent process.