Goal distance estimation for automated planning using neural networks and support vector machines

DOI10.1007/s11047-012-9332-yzbMath1334.68204OpenAlexW2000006123MaRDI QIDQ269064

Oliver Kramer, Benjamin Satzger

Publication date: 18 April 2016

Published in: Natural Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11047-012-9332-y

zbMATH Keywords

planningsearch heuristicregressionartificial neural networksupport vector machine

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)

Uses Software

• WEKA
• PDDL
• Graphplan

Cites Work

• Weighted \(A^*\) search - unifying view and application
• The computational complexity of propositional STRIPS planning
• Support-vector networks
• STRIPS: A new approach to the application of theorem proving to problem solving
• Improvements to Platt's SMO Algorithm for SVM Classifier Design
• Planning as heuristic search
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