An HL7-Aware Multi-agent System for Efficiently Handling Query Answering in an e-Health Context

2006 ◽  
pp. 967-974
Author(s):  
Pasquale De Meo ◽  
Gabriele Di Quarto ◽  
Giovanni Quattrone ◽  
Domenico Ursino
Keyword(s):  
Query Answering ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

A multi-agent system for efficiently managing query answering in an e-government scenario

2006 ◽  
Author(s):  
Pasquale De Meo ◽  
Giovanni Quattrone ◽  
Hind Fadil ◽  
Domenico Ursino
Keyword(s):  
Query Answering ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Intelligent Query Answering Mechanism in Multi Agent Systems

2011 ◽  
pp. 924-932
Author(s):  
Safiye Turgay ◽  
Fahrettin Yaman
Keyword(s):  
Evaluation Criteria ◽  
Evaluation Process ◽  
Query Answering ◽  
Rule Base ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Outer World ◽  
The Future ◽  
Multi Agent

The query answering system realizes the selection of the data, preparation, pattern discovering, and pattern development processes in an agent-based structure within the multi agent system, and it is designed to ensure communication between agents and an effective operation of agents within the multi agent system. The system is suggested in a way to process and evaluate fuzzy incomplete information by the use of fuzzy SQL query method. The modelled system gains the intelligent feature, thanks to the fuzzy approach and makes predictions about the future with the learning processing approach. The operation mechanism of the system is a process in which the agents within the multi agent system filter and evaluate both the knowledge in databases and the knowledge received externally by the agents, considering certain criteria. The system uses two types of knowledge. The first one is the data existing in agent databases within the system and the latter is the data agents received from the outer world and not included in the evaluation criteria. Upon receiving data from the outer world, the agent primarily evaluates it in knowledgebase, and then evaluates it to be used in rule base and finally employs a certain evaluation process to rule bases in order to store the knowledge in task base. Meanwhile, the agent also completes the learning process. This paper presents an intelligent query answering mechanism, a process in which the agents within the multi-agent system filter and evaluate both the knowledge in databases and the knowledge received externally by the agents. The following sections include some necessary literature review and the query answering approach Then follow the future trends and the conclusion.

Digital Circuit of Multi-Agent System for Two Pedestrian Streams in A Narrow Path

2014 ◽  
Vol 2 ◽  
pp. 471-474
Author(s):  
Takashi TOYOFUKU ◽  
Kunihiko MITSUBORI
Keyword(s):  
Digital Circuit ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Event-triggered and Self-triggered Formation Control of a Linear Multi-agent System

2020 ◽  
Vol 140 (3) ◽  
pp. 303-311
Author(s):  
Ryo Toyota ◽  
Kento Kotani ◽  
Toru Namerikawa
Keyword(s):  
Formation Control ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Event Triggered

The Mathematical Model of the Process for the Formation of Description of Local Security Threats in the Multi-Agent System

2004 ◽  
Vol 62 (1-6) ◽  
pp. 113-120
Author(s):  
A. V. Potapov ◽  
S. P. Yushchenko ◽  
A. T. Mirgaleev ◽  
I. B. Rodionov
Keyword(s):  
Mathematical Model ◽  
Security Threats ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
The Mathematical Model

Multi Agent System Approach for Shipboard Power System Reconfiguration

2009 ◽  
Vol 2 (4) ◽  
pp. 61-70
Author(s):  
Ravi Babu Pallikonda ◽  
◽  
K. Prapoorna ◽  
N.V. Prashanth ◽  
A. Shruti ◽  
...  
Keyword(s):  
Power System ◽  
System Approach ◽  
Multi Agent System ◽  
Agent System ◽  
System Reconfiguration ◽  
Shipboard Power System ◽  
Shipboard Power ◽  
Multi Agent

A MULTI-AGENT SYSTEM FOR MONITORING AND ANALYZING THE AIR QUALITY INDEX

2019 ◽  
Vol 18 (1) ◽  
pp. 147-157
Author(s):  
Elia Georgiana Dragomir
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Air Quality Index ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Consensus for Damaged Multi-agent System

2012 ◽  
Vol 38 (11) ◽  
pp. 1880 ◽  
Author(s):  
Wei-Sheng YAN ◽  
Jun-Bing LI ◽  
Yin-Tao WANG
Keyword(s):  
Multi Agent System ◽  
Agent System ◽  
Multi Agent
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