This is an extended abstract of the manuscript "A Lazy Approach to Neural Numerical Planning with Control Parameters" [René Heesch et al., 2024]. The paper presents a lazy, hierarchical approach to tackle the challenge of planning in complex numerical domains, where the effects of actions are influenced by control parameters, and may be described by neural networks.
@InProceedings{heesch_et_al:OASIcs.DX.2024.32, author = {Heesch, Ren\'{e} and Cimatti, Alessandro and Ehrhardt, Jonas and Diedrich, Alexander and Niggemann, Oliver}, title = {{Summary of "A Lazy Approach to Neural Numerical Planning with Control Parameters"}}, booktitle = {35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)}, pages = {32:1--32:3}, series = {Open Access Series in Informatics (OASIcs)}, ISBN = {978-3-95977-356-0}, ISSN = {2190-6807}, year = {2024}, volume = {125}, editor = {Pill, Ingo and Natan, Avraham and Wotawa, Franz}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2024.32}, URN = {urn:nbn:de:0030-drops-221243}, doi = {10.4230/OASIcs.DX.2024.32}, annote = {Keywords: Satisfiability Modulo Theory, Neural Numerical Planning with Control Parameters, Neural Networks} }
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