Solving relaxed problems is a commonly used technique in heuristic search to derive heuristic estimates. In heuristic planning, this is usually done by expanding a planning (reach...
Raquel Fuentetaja, Daniel Borrajo, Carlos Linares ...
Relaxed plans are used in the heuristic search planner FF for computing a numerical heuristic and extracting helpful actions. We present a novel way for extracting information fro...
Motion planning for mobile agents, such as robots, acting in the physical world is a challenging task, which traditionally concerns safe obstacle avoidance. We are interested in p...
We present an algorithm that quickly finds optimal plans for unforeseen agent preferences within graph-based planning domains where actions have deterministic outcomes and action ...
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...