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An Empirical Evaluation of Communication and Coordination Effectiveness in Autonomous Reactive Multiagent Systems (open access)

An Empirical Evaluation of Communication and Coordination Effectiveness in Autonomous Reactive Multiagent Systems

This thesis describes experiments designed to measure the effect of collaborative communication on task performance of a multiagent system. A discrete event simulation was developed to model a multi-agent system completing a task to find and collect food resources, with the ability to substitute various communication and coordination methods. Experiments were conducted to find the effects of the various communication methods on completion of the task to find and harvest the food resources. Results show that communication decreases the time required to complete the task. However, all communication methods do not fare equally well. In particular, results indicate that the communication model of the bee is a particularly effective method of agent communication and collaboration. Furthermore, results indicate that direct communication with additional information content provides better completion results. Cost-benefit models show some conflicting information, indicating that the increased performance may not offset the additional cost of achieving that performance.
Date: May 2005
Creator: Hurt, David
System: The UNT Digital Library
FP-tree Based Spatial Co-location Pattern Mining (open access)

FP-tree Based Spatial Co-location Pattern Mining

A co-location pattern is a set of spatial features frequently located together in space. A frequent pattern is a set of items that frequently appears in a transaction database. Since its introduction, the paradigm of frequent pattern mining has undergone a shift from candidate generation-and-test based approaches to projection based approaches. Co-location patterns resemble frequent patterns in many aspects. However, the lack of transaction concept, which is crucial in frequent pattern mining, makes the similar shift of paradigm in co-location pattern mining very difficult. This thesis investigates a projection based co-location pattern mining paradigm. In particular, a FP-tree based co-location mining framework and an algorithm called FP-CM, for FP-tree based co-location miner, are proposed. It is proved that FP-CM is complete, correct, and only requires a small constant number of database scans. The experimental results show that FP-CM outperforms candidate generation-and-test based co-location miner by an order of magnitude.
Date: May 2005
Creator: Yu, Ping
System: The UNT Digital Library