University of Basel, Research Group for Artificial Intelligence
Published August 4, 2021 | Version v2
Other Open

Supplementary Material for the ICAPS 2021 PRL Workshop Paper "Neural Network Heuristic Functions for Classical Planning: Reinforcement Learning and Comparison to Other Methods"

Creators

  • 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 (108.3 MB)

Name Size Download all
md5:08b6614d0d9520a5111d9c1009368828
108.3 MB Preview Download

Additional details

Funding

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