A Deep Reinforcement Learning based Approach to Learning Transferable Proof Guidance Strategies

Crouse Maxwell
Crouse Maxwell
Abdelaziz Ibrahim
Abdelaziz Ibrahim
Makni Bassem
Makni Bassem
Kapanipathi Pavan
Kapanipathi Pavan
Pell Edwin
Pell Edwin
Thost Veronika
Thost Veronika
Cited by: 0|Views47

Abstract:

Traditional first-order logic (FOL) reasoning systems usually rely on manual heuristics for proof guidance. We propose TRAIL: a system that learns to perform proof guidance using reinforcement learning. A key design principle of our system is that it is general enough to allow transfer to problems in different domains that do not share ...More

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