Problem Space Analysis for Plan Library Generation and Algorithm Selection in Real-time Systems

Computing solutions to intractable planning problems is particularly problematic within real-time domains. One approach to this problem includes off-line computation of contingency plans. However, because complex domains preclude creating a comprehensive library, a system must choose a subset of all possible plans to include. Strategic selections will ensure that the library contains an appropriate plan for encountered situations. This work discusses preliminary investigations into a scheme in which problem space analysis drives the creation of an efﬁcient plan library. For complex problems, an exact analysis of the problem space is not feasible, and an efﬁcient means of creating an approximate analysis is required. Thus, this work proposes the development of algorithms to efﬁciently generate and leverage the problem space analysis of complex planning problems.