Heuristic Guidance for Forward-Chaining Planning with Numeric Uncertainty

TY - CHAP

T1 - Heuristic Guidance for Forward-Chaining Planning with Numeric Uncertainty

AU - Marinescu, Liana Eleonora

AU - Coles, Andrew Ian

PY - 2016/6

Y1 - 2016/6

N2 - Uncertainty hinders many interesting applications of plan- ning – it may come in the form of sensor noise, unpredictable environments, or known limitations in problem models. In this paper we explore heuristic guidance for forward-chaining planning with continuous random variables, while ensuring a probability of plan success. We extend the Metric Relaxed Planning Graph heuristic to capture a model of uncertainty, providing better guidance in terms of heuristic estimates and dead-end detection. By tracking the accumulated error on nu- meric values, our heuristic is able to check if preconditions in the planning graph are achievable with a sufficient degree of confidence; it is also able to consider acting to reduce the accumulated error. Results indicate that our approach offers improvements in performance compared to prior work where a less-informed relaxation was used.

AB - Uncertainty hinders many interesting applications of plan- ning – it may come in the form of sensor noise, unpredictable environments, or known limitations in problem models. In this paper we explore heuristic guidance for forward-chaining planning with continuous random variables, while ensuring a probability of plan success. We extend the Metric Relaxed Planning Graph heuristic to capture a model of uncertainty, providing better guidance in terms of heuristic estimates and dead-end detection. By tracking the accumulated error on nu- meric values, our heuristic is able to check if preconditions in the planning graph are achievable with a sufficient degree of confidence; it is also able to consider acting to reduce the accumulated error. Results indicate that our approach offers improvements in performance compared to prior work where a less-informed relaxation was used.

KW - Artificial intelligence planning

KW - Uncertainty

M3 - Conference paper

SN - 9781577357575

BT - Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling

PB - AAAI Press

ER -