Symbolic perimeter abstraction heuristics for cost-optimal planning

DOI10.1016/j.artint.2018.02.002zbMath1445.68199OpenAlexW2792999547WikidataQ130097726 ScholiaQ130097726MaRDI QIDQ1647507

Carlos Linares López, Daniel Borrajo, Álvaro Á. Torralba

Publication date: 26 June 2018

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

Full work available at URL: https://doi.org/10.1016/j.artint.2018.02.002

zbMATH Keywords

abstraction heuristicsautomated planningcost-optimal planningsymbolic searchplanning systems

Mathematics Subject Classification ID

Specification and verification (program logics, model checking, etc.) (68Q60) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Uses Software

• CUDD

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Efficient symbolic search for cost-optimal planning
• Automatic construction of optimal static sequential portfolios for AI planning and beyond
• Optimal admissible composition of abstraction heuristics
• Depth-first iterative-deepening: An optimal admissible tree search
• Symbolic model checking: \(10^{20}\) states and beyond
• Automatically generating abstractions for planning
• \(\text{BIDA}^*\): An improved perimeter search algorithm
• Merge-and-Shrink Abstraction
• Graph-Based Algorithms for Boolean Function Manipulation
• Automated Creation of Pattern Database Search Heuristics
• Model Checking Software
• Planning as heuristic search

This page was built for publication: Symbolic perimeter abstraction heuristics for cost-optimal planning