Towards a Systematic Conflict Resolution Policy in Multi-agent System: A Conceptual Framework

2006 ◽  
pp. 274-283
Author(s):  
Yi Jiao ◽  
Baifeng Wu ◽  
Kun Zhu ◽  
Qiang Yu
Keyword(s):  
Conflict Resolution ◽  
Conceptual Framework ◽  
Multi Agent System ◽  
Agent System ◽  
System A ◽  
Multi Agent

Modeling of Multi-Agent System for Drilling Simulation

2011 ◽  
Vol 383-390 ◽  
pp. 1555-1561
Author(s):  
Wu Li Wang ◽  
Yan Jiang Wang
Keyword(s):  
Simulation System ◽  
Drilling Process ◽  
Multi Agent System ◽  
Agent System ◽  
Oil Drilling ◽  
Well Control ◽  
Existing Problems ◽  
System A ◽  
Multi Agent ◽  
Drilling Simulation

In view of the characteristics of the oil drilling process and the existing problems of traditional simulation system, a new distributed drilling simulation model was established based on Multi-Agent system (MAS) technology. By means of autonomous, cooperative and reactive characteristic of Agent, the drilling laws and phenomenon can be reflected promptly and accurately under any circumstances. The MAS modeling for oil drilling simulation, the structure and knowledge representation of each Agent and the communication among Agents are described in detail. Finally, an Agent-based normal drilling well control simulation training example was given. The simulation results show that the simulator based on Multi-Agent system has better performances than traditional drilling simulators, and enhances the integrated training function of the drilling simulation system.

Modernization of Healthcare and Medical Diagnosis System Using Multi Agent System (MAS)

2013 ◽  
pp. 592-622
Author(s):  
Shibakali Gupta ◽  
Sripati Mukherjee ◽  
Sesa Singha Roy
Keyword(s):  
Healthcare System ◽  
Appropriate Technology ◽  
Multi Agent System ◽  
Agent System ◽  
Healthcare Facilities ◽  
Loosely Coupled ◽  
System A ◽  
Multi Agent ◽  
Main Components ◽  
Medical Diagnosis System

The healthcare system that prevailed some years ago was a mere pen and paper based system. A number of workers, staff, and written records were the main components of the prevailing system of healthcare. This had a number of drawbacks, and a number of mishaps occurred due to mismanagement of data and information. There was a need for development. Then, the concept of telemedicine came, which revolutionized the healthcare paradigm to a great extent. With the advancement of telemedicine, many major problems of the prevailing system were removed. But, still there were many other aspects which could be further improved to make healthcare facilities more enhanced. Keeping this in mind, the concept of Multi Agent System (MAS) was introduced in the healthcare system later. MASes are considered as the best and most appropriate technology that can be used in the development of applications in healthcare paradigm where the presence of multiple agents, heterogeneous and loosely coupled components, the data management in a dynamic and distributed environment, and multi-user collaborations are considered the most pertinent requirements for healthcare system. This chapter focuses mainly about MAS, its applications, and some systems that were developed by the authors.

Modernization of Healthcare and Medical Diagnosis System Using Multi Agent System (MAS)

2015 ◽  
pp. 1426-1455
Author(s):  
Shibakali Gupta ◽  
Sripati Mukherjee ◽  
Sesa Singha Roy
Keyword(s):  
Healthcare System ◽  
Appropriate Technology ◽  
Multi Agent System ◽  
Agent System ◽  
Healthcare Facilities ◽  
Loosely Coupled ◽  
System A ◽  
Multi Agent ◽  
Main Components ◽  
Medical Diagnosis System

The healthcare system that prevailed some years ago was a mere pen and paper based system. A number of workers, staff, and written records were the main components of the prevailing system of healthcare. This had a number of drawbacks, and a number of mishaps occurred due to mismanagement of data and information. There was a need for development. Then, the concept of telemedicine came, which revolutionized the healthcare paradigm to a great extent. With the advancement of telemedicine, many major problems of the prevailing system were removed. But, still there were many other aspects which could be further improved to make healthcare facilities more enhanced. Keeping this in mind, the concept of Multi Agent System (MAS) was introduced in the healthcare system later. MASes are considered as the best and most appropriate technology that can be used in the development of applications in healthcare paradigm where the presence of multiple agents, heterogeneous and loosely coupled components, the data management in a dynamic and distributed environment, and multi-user collaborations are considered the most pertinent requirements for healthcare system. This chapter focuses mainly about MAS, its applications, and some systems that were developed by the authors.

scholarly journals Network resources management in a multi-agent system: A simulative approach

2010 ◽  
Vol 106 (9/10) ◽  
Author(s):  
Emmanuel A. Olajubu ◽  
Ganiyu A. Aderounmu ◽  
Emmanuel R. Adagunodo
Keyword(s):  
Multi Agent System ◽  
Network Resources ◽  
Agent System ◽  
Resources Management ◽  
System A ◽  
Multi Agent

INTENT RECOGNITION IN MULTI-AGENT SYSTEMS: COW HERDING

2014 ◽  
Vol 28 (05) ◽  
pp. 1459006
Author(s):  
NAJLA AHMAD ◽  
ARVIN AGAH
Keyword(s):  
Conceptual Framework ◽  
Recognition System ◽  
Plan Recognition ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Intent Recognition ◽  
Domain Specific ◽  
Novel Approach ◽  
Multi Agent

In a multi-agent system, an agent may utilize its idle time to assist other agents in the system. Intent recognition is proposed to accomplish this with minimal communication. An agent performing recognition observes the tasks other agents are performing and, unlike the much studied field of plan recognition, the overall intent of an agent is recognized instead of a specific plan. The observing agent may use capabilities that it has not observed. A conceptual framework is proposed for intent recognition systems. An implementation of the conceptual framework is tested and evaluated. We hypothesize that using intent recognition in a multi-agent system increases utility (where utility is domain specific) and decreases the amount of communication. We test our hypotheses using the domain of Cow Herding, where agents attempt to herd cow agents into team corrals. A set of metrics, including task time and number of communications, is used to compare the performance of plan recognition and intent recognition. In our results, we find that intent recognition agents communicate fewer times than plan recognition agents. In addition, unlike plan recognition, when agents use the novel approach of intent recognition, they select unobserved actions to perform. Intent recognition agents were also able to outperform plan recognition agents by consistently scoring more points in the Cow Herding domain. This research shows that under certain conditions, an intent recognition system is more efficient than a plan recognition system. The advantage of intent recognition over plan recognition becomes more apparent in complex domains.

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