A Method For Improving Decentralized Task Allocation For Multiagent Systems in Low-Communication Environments.

Abstract

Communication is an important aspect of task allocation, but it has a cost and low communication restricts the information exchange needed for task allocation. As a result, a lot of decentralized task allocation algorithms perform worse as communication worsens. The contribution of this thesis is a method to improve the performance of a task allocation algorithm in low-communication environments and reduce the cost of communication by restricting communication. This method, applied to the Consensus Based Auction Algorithm (CBAA), determines when an agent should communicate and estimates the information that will be received from other agents. This method is compared to other decentralized task allocation algorithms at different levels of communication in a ship protection scenario. Results show that this method when applied to CBAA performs comparably to CBAA while reducing communication.