Ontology and Terminology Servers in Agent-based Health-care Information Systems

1997 ◽  
Vol 36 (01) ◽  
pp. 30-43 ◽  
Author(s):  
G. Lanzola ◽  
M. Stefanelli ◽  
S. Falasconi
Keyword(s):  
Health Care ◽  
Information System ◽  
Distributed Applications ◽  
Multi Agent System ◽  
Health Care Information ◽  
Agent System ◽  
Semantic Coherence ◽  
Architectural Framework ◽  
Care Information ◽  
Multi Agent

Abstract:A new research paradigm is emerging based on the multi-agent system architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. Within a multi-agent system, the different “views of the world” of knowledgeable agents are to be bridged through their commitment to common ontologies and terminologies. We developed a general methodology for the design or integration of new components into a Health-care Information System conceived as a network of software and human agents. In our view, ontological and terminological services are entrusted to dedicated agents, namely ontology and terminology servers, allowing the configuration of suitable application ontologies for distributed applications. The role is described that such servers, operatively coordinated in order to preserve semantic coherence, should play within a distributed Health-care Information System.

A Simulation Approach for Analyzing MAS Model of SIS

2012 ◽  
Vol 468-471 ◽  
pp. 173-180
Author(s):  
Yi Ning Song ◽  
Zhi Li
Keyword(s):  
Information System ◽  
Modeling And Simulation ◽  
Longitudinal Analysis ◽  
Satellite System ◽  
Model Structure ◽  
Multi Agent System ◽  
Simulation Approach ◽  
Agent System ◽  
Agent Model ◽  
Multi Agent

The purpose of this paper is to explore the effective approach of Multi-Agent system(MAS) modeling and simulation. A detailed study of modeling and simulation of Space Information System has been carried out by combining controlled and intelligent requirements. To begin with we will provide a brief background on the Multi-Agent System concept and structure. Furthermore, grasp the model structure through vertical and longitudinal analysis with the consideration of emergence and collaboration. In addition, we described the Multi-agent model for Space Information System(SIS). Finally, algorithms of realizing the collaboration structures of the communication satellite system that presented in this paper were described.

Planning Agent for Geriatric Residences

2011 ◽  
pp. 1316-1322 ◽  
Author(s):  
Javier Bajo ◽  
Dante I. Tapia ◽  
Sara Rodríguez ◽  
Juan M. Corchado
Keyword(s):  
Health Care ◽  
Radio Frequency Identification ◽  
Adaptive Systems ◽  
Autonomous Agent ◽  
Case Based Reasoning ◽  
Multi Agent System ◽  
Agent System ◽  
Learning And Adaptation ◽  
Multi Agent ◽  
Case Based

Agents and Multi-Agent Systems (MAS) have become increasingly relevant for developing distributed and dynamic intelligent environments. The ability of software agents to act somewhat autonomously links them with living animals and humans, so they seem appropriate for discussion under nature-inspired computing (Marrow, 2000). This paper presents AGALZ (Autonomous aGent for monitoring ALZheimer patients), and explains how this deliberative planning agent has been designed and implemented. A case study is then presented, with AGALZ working with complementary agents into a prototype environment-aware multi-agent system (ALZ-MAS: ALZheimer Multi-Agent System) (Bajo, Tapia, De Luis, Rodríguez & Corchado, 2007). The elderly health care problem is studied, and the possibilities of Radio Frequency Identification (RFID) (Sokymat, 2006) as a technology for constructing an intelligent environment and ascertaining patient location to generate plans and maximize safety are examined. This paper focuses in the development of natureinspired deliberative agents using a Case-Based Reasoning (CBR) (Aamodt & Plaza, 1994) architecture, as a way to implement sensitive and adaptive systems to improve assistance and health care support for elderly and people with disabilities, in particular with Alzheimer. Agents in this context must be able to respond to events, take the initiative according to their goals, communicate with other agents, interact with users, and make use of past experiences to find the best plans to achieve goals, so we propose the development of an autonomous deliberative agent that incorporates a Case-Based Planning (CBP) mechanism, derivative from Case-Based Reasoning (CBR) (Bajo, Corchado & Castillo, 2006), specially designed for planning construction. CBP-BDI facilitates learning and adaptation, and therefore a greater degree of autonomy than that found in pure BDI (Believe, Desire, Intention) architecture (Bratman, 1987). BDI agents can be implemented by using different tools, such as Jadex (Pokahr, Braubach & Lamersdorf, 2003), dealing with the concepts of beliefs, goals and plans, as java objects that can be created and handled within the agent at execution time.

OVACARE: A Multi-Agent System for Assistance and Health Care

2010 ◽  
pp. 318-327 ◽  
Author(s):  
Juan F. De Paz ◽  
Sara Rodríguez ◽  
Javier Bajo ◽  
Juan M. Corchado ◽  
Emilio S. Corchado
Keyword(s):  
Health Care ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent
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