98 citations · 647 across the 44 of their papers we have counts for
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cs.AI2022
Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis
Jonathan Laurent, André Platzer
We propose a new approach to automated theorem proving where an AlphaZero-style agent is self-training to refine a generic high-level expert strategy expressed as a nondeterministi…
cs.AI2019★ 40 cited
Verifiably Safe Off-Model Reinforcement Learning
Nathan Fulton, Andre Platzer
The desire to use reinforcement learning in safety-critical settings has inspired a recent interest in formal methods for learning algorithms. Existing formal methods for learning…