We investigate the problem of temporal planning with concurrent actions having stochastic durations, especially in the context of extended-state-space based planners. The problem ...
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 present a new approach to optimal rectangle packing, an NP-complete problem that can be used to model many simple scheduling tasks. Recent attempts at incorporating artificial ...
Planning is often not a one-shot task because either the world or the agent's knowledge of the world changes. In this paper, we introduce a new principle that can be used to ...
In AI Planning, as well as Verification, a successful method is to compile the application into boolean satisfiability (SAT), and solve it with state-of-the-art DPLL-based procedu...
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Classical planning algorithms require that their operators be simple in order for planning to be tractable. However, the complexities of real world domains suggest that, in order ...
We investigate a task insertion heuristic for oversubscribed scheduling problems, max-availability, that uses a simple estimate of resource contention to assign tasks to intervals...
The 3rd and 4th International Planning Competitions have enriched the set of benchmarks for classical propositional planning by a number of novel and interesting planning domains....