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Published August 4, 2021 | Version v1
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Supplementary Material for the ICAPS 2021 PRL Workshop Paper "Neural Network Heuristic Functions for Classical Planning: Reinforcement Learning and Comparison to Other Methods"

  • 1. University of Basel
  • 2. Australian National University
  • 3. Saarland University

Description

This repositories contains the code, benchmarks, and the experimental results for the ICAPS 2021 PRL Workshop paper "Neural Network Heuristic Functions for Classical Planning: Reinforcement Learning and Comparison to Other Methods" by Patrick Ferber, Florian Geißer, Felipe Trevizan, Malte Helmert, and Jörg Hoffmann.

Files

ferber-et-al-icaps2021wsprl-supplement.zip

Files (108.1 MB)

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Additional details

Funding

Certified Correctness and Guaranteed Performance for Domain-Independent Planning (CCGP-Plan) 200021_182107
Swiss National Science Foundation