|M.Sc Student||Ben-Ami David|
|Subject||A Comparative Evaluation of Agent Location Mechanisms in|
Large Scale MAS
|Department||Department of Industrial Engineering and Management||Supervisors||Professor Shay Kutten|
|Dr. Onn Shehory|
Our project concerns the design of internal mechanisms of multi-agent systems. Multi-agent systems have emerged as one of the important areas of research and development in information technology in the 1990s. A multi-agent system is one composed of multiple interacting software components known as agents, which are typically capable of co-operating to solve problems that are beyond the abilities of any individual member. An agent is an autonomous software unit that can interact with and influences its environment. Multi-agent systems are important primarily because they have been found to have very wide applicability, in areas as diverse as industrial process control and electronic commerce.
Agents in open multi-agent systems (MAS) need means for locating other agents with which they may collaborate. To address this need, several agent location mechanisms were suggested. Two major approaches dominate agent location mechanisms: a centralized approach using middle agents, and a distributed, peer-to-peer approach. Agent designers, when designing agents to be part of open MAS, should consider these approaches, to provide the agents with appropriate agent location capabilities. However, selecting an agent location approach, let alone a specific solution, is a nontrivial task. In this study we address this difficulty. We perform a systematic comparative evaluation of agent location approaches. We measure the performance of these approaches subject to various MAS configurations. We draw conclusions regarding the conditions in which each approach is preferable. Prior evaluations fall short in addressing realistic MAS settings. In particular, our evaluation is the first to examine scalability of agent location mechanisms in terms of both system size (thousands of agents) and network distribution (over multiple hosts).