A Role-Based Architecture for Intelligent Agent Systems

2006 ◽  
Author(s):  
Haibin Zhu
Keyword(s):  
Intelligent Agent ◽  
Agent Systems ◽  
Role Based

Role-Based Multi-Agent Systems

2011 ◽  
pp. 254-285 ◽  
Author(s):  
Haibin Zhu ◽  
MengChu Zhou
Keyword(s):  
System Design ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Collaborative Behavior ◽  
Cooperative Agents ◽  
Multi Agent ◽  
Role Based ◽  
Information Personalization

Agent system design is a complex task challenging designers to simulate intelligent collaborative behavior. Roles can reduce the complexity of agent system design by categorizing the roles played by agents. The role concepts can also be used in agent systems to describe the collaboration among cooperative agents. In this chapter, we introduce roles as a means to support interaction and collaboration among agents in multi-agent systems. We review the application of roles in current agent systems at first, then describe the fundamental principles of role-based collaboration and propose the basic methodologies of how to apply roles into agent systems (i.e., the revised E-CARGO model). After that, we demonstrate a case study: a soccer robot team designed with role specifications. Finally, we present the potentiality to apply roles into information personalization.

Adaptive Collaboration Based on the E-CARGO Model

2012 ◽  
Vol 4 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Haibin Zhu ◽  
Ming Hou ◽  
Mengchu Zhou
Keyword(s):  
Team Performance ◽  
Theoretical Foundation ◽  
Multi Agent Systems ◽  
Role Assignment ◽  
Future Studies ◽  
Agent Systems ◽  
Multi Agent ◽  
Computer Based ◽  
Single Controller ◽  
Role Based

Adaptive Collaboration (AC) is essential for maintaining optimal team performance on collaborative tasks. However, little research has discussed AC in multi-agent systems. This paper introduces AC within the context of solving real-world team performance problems using computer-based algorithms. Based on the authors’ previous work on the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model, a theoretical foundation for AC using a simplified model of role-based collaboration (RBC) is proposed. Several parameters that affect team performance are defined and integrated into a theorem, which showed that dynamic role assignment yields better performance than static role assignment. The benefits of implementing AC are further proven by simulating a “future battlefield” of remotely-controlled robotic vehicles; in this scenario, team performance clearly benefits from shifting vehicles (or roles) using a single controller. Related research is also discussed for future studies.

A Mobile Intelligent Agent-Based Architecture for E-Business

2009 ◽  
pp. 712-728
Author(s):  
Zhiyong Weng ◽  
Thomas Tran
Keyword(s):  
Mobile Devices ◽  
Intelligent Agent ◽  
Personal Digital Assistant ◽  
The Internet ◽  
Agent Based ◽  
Agent Systems ◽  
Business Architecture ◽  
Remote Locations ◽  
Flexible Architecture ◽  
High Scalability

This article proposes a mobile intelligent agentbased e-business architecture that allows buyers and sellers to perform business at remote locations. An e-business participant can generate a mobile, intelligent agent via some mobile devices (such as a personal digital assistant or mobile phone) and dispatch the agent to the Internet to do business on his/her behalf. This proposed architecture promises a number of benefits: First, it provides great convenience for traders as business can be conducted anytime and anywhere. Second, since the task of finding and negotiating with appropriate traders is handled by a mobile, intelligent agent, the user is freed from this time-consuming task. Third, this architecture addresses the problem of limited and expensive connection time for mobile devices: A trader can disconnect a mobile device from its server after generating and launching a mobile intelligent agent. Later on, the trader can reconnect and call back the agent for results, therefore minimizing the connection time. Finally, by complying with the standardization body FIPA, this flexible architecture increases the interoperability between agent systems and provides high scalability design for swiftly moving across the network.

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