AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will tra...
Conformant planning is a variation of classical AI planning where the initial state is partially known and actions can have nondeterministic effects. While a classical plan must a...
In our experiments with four well-known systems for solving partially observable planning problems (Contingent-FF, MBP, PKS, and POND), we were greatly surprised to find that they...
Ronald Alford, Ugur Kuter, Dana S. Nau, Elnatan Re...
We study the partitioning of temporal planning problems formulated as mixed-integer nonlinear programming problems, develop methods to reduce the search space of partitioned subpr...
Generating production-quality plans is an essential element in transforming planners from research tools into real-world applications. However most of the work to date on learning...