SemML
In this project we develop learning-based exploration heuristics for LTL Synthesis that exploit the semantic labelling of the underlying Automaton/Game. The current version of the tool is available on Gitlab.
Team
Research Area
Machine Learning for LTL Synthesis
We apply machine learning to the LTL synthesis problem.
Publications
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2025 |
SemML: Enhancing Automata-Theoretic LTL Synthesis with Machine Learning
Tools and Algorithms for the Construction and Analysis of Systems - 31st International Conference, TACAS 2025, Held as Part of the International Joint Conferences on Theory and Practice of Software, ETAPS 2025, Hamilton, ON, Canada, May 3-8, 2025, Proceedings, Part I |