MAPLE: Multi-Agent Planning, Learning, and Execution
Abstract : The fundamental problems addressed in this report pertained to the coordination of multi-agent software systems acting in dynamic, physical environments. The Multi-Agent Planning MAPLE project focused on the development and evaluation of new algorithms for integrating information and for coordinating the actions of large multi-agent teams. Three different aspects of multi-agent systems are in this report. First, this project developed a prototype of a secure decentralized database, which made it possible to disperse information among multiple agents in a secure and scalable way. Second, the project developed a multi-agent system for acquiring and integrating information in large dynamic environments. Third was a planning and multi-agent coordination technique for enabling large teams of autonomous agents to perform missions in highly dynamic and partially observable environments. The resulting algorithms were implemented and evaluated predominately using a simulator called "MapleSim", which simulated the country of Honduras after the devastation caused by Hurricane Mitch in 1998.