Satisficing Strategies for Resource - Limited Policy

This work examines the problem of searching for schedulable real-time control policies for resource-limited agents acting in dynamic environments. The dynamic properties of the environment and resource limitations of the agent render the problem of solving for an optimal policy infeasible. We therefore limit our search to a satisficing, rather than an optimal policy. We view the policy search as a search for a state reachability graph, with an action assigned to each of the states in the graph. The search algorithm takes advantage of the properties of the reachability graphs to propagate failure conditions from inherent failure states to other states in the reachability graph, which allows us to exploit some techniques used in constraint satisfaction problems to quickly remove some unacceptable policies from consideration. Our analysis and experiments show that, under certain conditions, we can use backtracking and memoization techniques that significantly improve the efficiency of the search algorithm.