Authors:
D. Oviedo
;
M. C. Romero-Ternero
;
M. D. Hernández
;
A. Carrasco
;
F. Sivianes
and
J. I. Escudero
Affiliation:
Universidad de Sevilla, Spain
Keyword(s):
Multi-agent system, Knowledge sharing, Knowledge spreading, Ontologies (artificial intelligence), Open systems, Software engineering, Agent communication, Automatic control system, Interoperability model.
Related
Ontology
Subjects/Areas/Topics:
Agent-Oriented Programming
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Coordination in Multi-Agent Systems
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Intelligent Agents
;
Intelligent Control Systems and Optimization
;
Internet Technology
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge Management
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Software Engineering
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
This paper presents a model to spread knowledge in multiagent-based control systems, where simplicity, scalability, flexibility and optimization of communications system are the main goals. This model not only implies some guidelines on how the communication among different agents in the system is carried out, but also defines the organization of the elements of the system. The proposed model is applied to a control system of a solar power plant, obtaining an architecture which optimizes agents for the problem. The agents in this
system can cooperate and coordinate to achieve a global goal, encapsulate the hardware interfaces and make the control system easily adapt to different requirements through configuration. The model also includes an algorithm that adds new variables in the communication among agents and enables flow control knowledge in the system.