44 citations · 53 across the 4 of their papers we have counts for
4 papers
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
Minchao Wu, Michael Norrish, Christian Walder +1
We propose a novel approach to interactive theorem-proving (ITP) using deep reinforcement learning. The proposed framework is able to learn proof search strategies as well as tacti…
Corpus Distillation for Effective Fuzzing: A Comparative Evaluation
Adrian Herrera, Hendra Gunadi, Liam Hayes +5
Mutation-based fuzzing typically uses an initial set of non-crashing seed inputs (a corpus) from which to generate new inputs by mutation. A corpus of potential seeds will often co…
TacticToe: Learning to Prove with Tactics
Thibault Gauthier, Cezary Kaliszyk, Josef Urban +2
We implement a automated tactical prover TacticToe on top of the HOL4 interactive theorem prover. TacticToe learns from human proofs which mathematical technique is suitable in eac…
Reasoning with Data-Centric Business Processes
Andreas Bauer, Peter Baumgartner, Michael Norrish
We describe an approach to modelling and reasoning about data-centric business processes and present a form of general model checking. Our technique extends existing approaches, wh…