Improving the agent-oriented modeling process by roles
Proceedings of the fifth international conference on Autonomous agents
ROADMAP: extending the gaia methodology for complex open systems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Prometheus: a methodology for developing intelligent agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
The Gaia Methodology for Agent-Oriented Analysis and Design
Autonomous Agents and Multi-Agent Systems
A Method for Agent-Based System Requirements Analysis
MSE '02 Proceedings of the Fourth IEEE International Symposium on Multimedia Software Engineering
An Enhanced Model For Agent Based Requirement Gathering And Pre-System Analysis
ECBS '06 Proceedings of the 13th Annual IEEE International Symposium and Workshop on Engineering of Computer Based Systems
A hybrid model for agent based system requirements analysis
ACM SIGSOFT Software Engineering Notes
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In this paper, we propose a system performance-efficient clustering and mapping algorithm for agent-based system. Optimal cluster size is obtained by user-defined performance parameter (η).This presents a novel systematic approach to optimize the system performance by exploiting the relationships and dependencies among roles as well as clustering of roles and mapping criteria between roles to agents. The concept of roles has been advocated to model application domain agents, which evolve dynamically during their lifespan. These agents may acquire new roles and drop old roles in order to comply with the requirements, where as each role and their instances are associated during the whole lifespan. The concept of clustering of role and mapping the role to agent by analyzing Interaction among Roles, Resource Dependencies among Roles and Relationship among Roles is presented in this paper.