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...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...
Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic gu...