Improving Heuristics On-the-fly for Effective Search in Plan Space

Autor:	Deepak Khemani, Shashank Shekhar
Rok vydání:	2015
Předmět:	Mathematical optimization Heuristic On the fly Computer science Plan (drawing) Space (commercial competition) Planner Adaptation (computer science) Heuristics computer Domain (software engineering) computer.programming_language
Zdroj:	KI 2015: Advances in Artificial Intelligence ISBN: 9783319244884 KI
DOI:	10.1007/978-3-319-24489-1_27
Popis:	The design of domain independent heuristic functions often brings up experimental evidence that different heuristics perform well in different domains. A promising approach is to monitor and reduce the error associated with a given heuristic function even as the planner solves a problem. We extend this single-step-error adaptation to heuristic functions from Partial Order Causal Link (POCL) planning. The goal is to allow a partial order planner to observe the effective average-step-error during search. The preliminary evaluation shows that our approach improves the informativeness of the state-of-the-art heuristics. Our planner solves more problems by using the improved heuristics as compared to when it uses current heuristics in the selected domains.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cae824c4ae3ab543dc2b994f59b4f686 https://doi.org/10.1007/978-3-319-24489-1_27 Zobrazit plný text záznamu