Simulation-based planning in support of multi-agent scenarios

Whenever a simulation involves multiple interacting intelligent objects, called agents, there is the issue of how to code the decision making procedures that drive the agents. The usual method of encoding decision-making procedures has been to use operator or rule-based models, representing the decision making intelligence of the coordi nator i.e., commander on a battlefield If the purpose of the simulation is to precisely emulate a particular coordinator's intelligence, then such rule-based models may often be most appropriate. The goal, however is often to win the engagement or have the agents perform a task to the satisfaction of an optimal condition. In these cases, we have created a methodology, simulation-based planning, that embeds one simulation inside another. The embedded simulation simulates the actions of agents and intentions of coordinators before committing to a plan. Plan alternatives are generated based on discrete paths through spatial regions of a domain, while specific optimal plans are generated through the use of experimental design and simulation. We have found that, through simulation-based planning, near-optimal plans can be constructed by using simulation, in addition to using simulation once a plan has been adopted. In the case of semi-automated force development, this involves embedding the simulation-based planner inside the computer generated force simulation. These results point to extensions for simulation-based planning beyond the military domain.