Catálogo de publicaciones - libros

Intelligent Tutoring Systems (ITSs) base their interoperability on the interchange of domain knowledge about learning and teaching processes and about students. To enable the interchange of domain knowledge between ITSs and heterogeneous Health Information Systems (HIS) we propose a multi-agent architecture allowing sharing patient’s clinical data in Health Information Systems. The Health Level (HL7) is used as a standard messaging protocol for collecting the clinical patient data distributed over Health Information Systems.

The issue of multi-agent planning in highly dynamic environments is a major impediment to conventional planning solutions. Plan repair and replanning solutions alike have difficulty adapting to frequently changing environment states. To adequately handle such situations, this paper instead focuses on preserving individual agent plans through multi-agent coordination techniques. We describe a reactive agent system architecture in which the main focus of an agent is to be able to achieve its subgoals without interfering with any other agent. The system is a 3-level architecture, where each level is guided by the following fundamental principles, respectively: is it valid to generate a plan for a subgoal, is most appropriate for completing the subgoal, and should the plan be carried out.

Ontology matching plays a vital role in a number of areas, such as knowledge integration, services composition or system interoperability. In this paper we present an architectural overview of an ontological service, wrapped up as an Ontology Agent, supporting automated ontology matching and facilitating inter-agent communication.

To allow for flexibility in software structures (architectures) especially plugins and agents are proposed solutions. While plugins are used to support the conceptual and practical issues within component oriented software environments, agents are used in software areas where social metaphors like (self-)adaptability, flexibility, mobility, interactivity etc. are of interest. Common to both approaches is a strong relation to a service-oriented view on exporting functionality. This contribution illustrates the idea of the integration of both concepts on the formal basis of high-level Petri nets.

This work focuses on the problem of inventory management which is an important element of the supply-chain management challenge. The goal of our research was to develop an application which supports decision making regarding optimal strategies for producing electrical machines. The multi-agent approach offers several valuable features which may be exploited for supply-chains management: problem decentralization, isolation of different kinds of sub–problems and solving them separately, as well as modeling and predicting the behavior of the particular modules and referring to the means offered by distributed intelligence.

Resource allocation in distributed systems is an exciting area of research. Inherent properties in this environment, such as strategic users acting selfishly and the structure of the environment within which exchanges occur, are relevant challenges to study. This paper proposes a market–based resource allocation in a distributed environment and explores the effects of network structure on the allocation of performance together. Further, we proposed mechanisms to improve the performance of the market. The proposed model, as well as mechanisms to maximize the allocation of objects/goods have been implemented and studied experimentally. The results obtained show how topology affects the performance of the market. Using information propagation mechanisms clearly contributes to its improvement.