State space search nogood learning: online refinement of critical-path dead-end detectors in planning

DOI10.1016/j.artint.2016.12.002zbMath1402.68165OpenAlexW2567147741MaRDI QIDQ514137

Jörg Hoffmann, Marcel Steinmetz

Publication date: 28 February 2017

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2016.12.002

zbMATH Keywords

planningsearchheuristic search

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Online Relaxation Refinement for Satisficing Planning: On Partial Delete Relaxation, Complete Hill-Climbing, and Novelty Pruning

Uses Software

• MiniSat
• STAN
• SPIN
• Walksat
• Chaff
• Graphplan
• TorchLight

Cites Work

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