Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators

Recent advances in reinforcement learning (RL) have led to a growing interest in applying RL to classical planning domains or applying classical planning methods to some complex RL domains. However, the long-horizon goal-based problems found in classical planning lead to sparse rewards for RL, makin...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Gehring, Clement, Asai, Masataro, Chitnis, Rohan, Silver, Tom, Kaelbling, Leslie Pack, Sohrabi, Shirin, Katz, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!