Estefania Argente

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.

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.

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.

An open architecture for service-oriented virtual organizations

Recent technological advances in open systems have imposed new needs on multi-agent systems. Nowadays, open systems require open autonomous scenarios in which heterogeneous entities (agents or services) interact to fulfill the system goals. The main contribution of this paper is the definition of an open architecture and computational model for largescale open multi-agent systems based on a service-oriented approach. This work requires a high-level design of all features and needs for systems of this kind. The new proposed architecture, called THOMAS, is specifically addressed for the design of virtual organizations. A simplified example for the management of a travel agency system, which shows the features of the proposal, is also included.

Open issues for normative multi-agent systems

A challenging problem currently addressed in the multi-agent systems area is the development of open systems; which are characterized by the heterogeneity of their participants and the dynamic features of both their participants and their environment. The main feature of agents in these systems is autonomy. It is this autonomy that requires regulation, and norms are a solution for this. Norms represent a tool for achieving coordination and cooperation among the members of a society. They have been employed in the field of Artificial Intelligence as a formal specification of deontic statements aimed at regulating the actions of software agents and the interactions among them. This article gives an overview of the most relevant works on norms for multi-agent systems. This review considers open multi-agent systems challenges and points out the main open questions that remain in norm representation, reasoning, creation, and implementation.

GORMAS: an organizational-oriented methodological guideline for open MAS

An Organizational-Oriented Methodological Guideline for designing Virtual Organizations, focused on Service-Oriented Open Multi-Agent Systems, is presented in this paper. This guideline covers the requirement analysis, the structure design and the organization-dynamics design steps, in which software designers mainly specify the services that the system under study is requested to offer, the internal structure of this system and the norms that control its behavior, taking into account the specific features of open multi-agent systems.

Designing Virtual Organizations

Virtual Organizations are a suitable mechanism for enabling coordination of heterogeneous agents in open environments. Taking into account many concepts of the Human Organization Theory, a model for Virtual Organizations has been developed. This model describes the structural, functional, normative and environmental aspects of the system. It is based on four main concepts: organizational unit, service, norm and environment. All these concepts have been applied in a case-study example for the management of a travel agency system.

Supporting Agent Organizations

Organizational Theory concepts have been adapted to improve, extend and facilitate Agent Organizations modeling. Thus, three basic organizational topologies from which other more complex organizations can be composed have been identified. Moreover, this organizational modeling has been implemented in a specific MAS platform (SPADE) making use of Multiuser Conference technology. We have also defined several services for SPADE that ease the implementation of organization dynamics, such as member access and agent interaction control.

Neural networks for modelling of kinetic reaction data applicable to catalyst scale up and process control and optimisation in the frame of combinatorial catalysis

Abstract This work describes an application of artificial neural networks (ANNs) for modelling the kinetics of catalytic reactions using methods not based on fundamental knowledge. Thus, neural networks have been used to model the behaviour of different reactions under different reactor conditions. The modelling of catalytic reactions by neural networks has been demonstrated, and the influence of experimental error in input data has been estimated. In addition, a novel methodology for modelling catalytic data employing already-trained neural networks has been systematically studied by using experimental results from the catalytic hydroisomerization of different n -paraffins. It can be then expected that a new reaction system can be rapidly analysed with a small number of experiments if a library of well-trained neural networks which represent a series of different reaction networks is constructed.