Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement Learning

20 July 2018

Papers citing "Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement Learning"

24 / 24 papers shown

Title
Graph Neural Reasoning May Fail in Certifying Boolean Unsatisfiability Ziliang Chen Zhanfu Yang NAI AI4CE 33 5 0 25 Sep 2019
Exact Combinatorial Optimization with Graph Convolutional Neural Networks Maxime Gasse Didier Chételat Nicola Ferroni Laurent Charlin Andrea Lodi GNN CML 119 483 0 04 Jun 2019
Graph Representations for Higher-Order Logic and Theorem Proving Aditya Sanjay Paliwal Sarah M. Loos M. Rabe Kshitij Bansal Christian Szegedy AI4CE NoLa 131 98 0 24 May 2019
Learning to Prove Theorems via Interacting with Proof Assistants Kaiyu Yang Jia Deng AIMat LRM 93 144 0 21 May 2019
Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers Zhanfu Yang Fei Wang Ziliang Chen Guannan Wei Tiark Rompf NAI GNN 20 7 0 27 Apr 2019
HOList: An Environment for Machine Learning of Higher-Order Theorem Proving Kshitij Bansal Sarah M. Loos M. Rabe Christian Szegedy S. Wilcox AIMat 44 51 0 05 Apr 2019
Guiding High-Performance SAT Solvers with Unsat-Core Predictions Daniel Selsam Nikolaj S. Bjørner NAI 53 121 0 12 Mar 2019
Coloring Big Graphs with AlphaGoZero Jiayi Huang Md. Mostofa Ali Patwary G. Diamos AI4CE GNN 42 49 0 26 Feb 2019
Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning M. Kusumoto Keisuke Yahata Masahiro Sakai AIMat LRM 44 11 0 02 Nov 2018
GamePad: A Learning Environment for Theorem Proving Daniel Huang Prafulla Dhariwal D. Song Ilya Sutskever 73 110 0 02 Jun 2018
Reinforcement Learning of Theorem Proving C. Kaliszyk Josef Urban Henryk Michalewski Miroslav Olsák 34 148 0 19 May 2018
Learning to Reason with HOL4 tactics Thibault Gauthier C. Kaliszyk Josef Urban 55 77 0 02 Apr 2018
Can Neural Networks Understand Logical Entailment? Richard Evans D. Saxton David Amos Pushmeet Kohli Edward Grefenstette NAI 142 128 0 23 Feb 2018
Learning a SAT Solver from Single-Bit Supervision Daniel Selsam Matthew Lamm Benedikt Bünz Percy Liang L. D. Moura D. Dill NAI 90 422 0 11 Feb 2018
Learning to Represent Programs with Graphs Miltiadis Allamanis Marc Brockschmidt Mahmoud Khademi GNN NAI 109 799 0 01 Nov 2017
Premise Selection for Theorem Proving by Deep Graph Embedding Mingzhe Wang Yihe Tang Jian Wang Jia Deng 54 133 0 28 Sep 2017
Learning Combinatorial Optimization Algorithms over Graphs H. Dai Elias Boutros Khalil Yuyu Zhang B. Dilkina Le Song 101 1,460 0 05 Apr 2017
Deep Network Guided Proof Search Sarah M. Loos G. Irving Christian Szegedy C. Kaliszyk AIMat 66 159 0 24 Jan 2017
Learning Continuous Semantic Representations of Symbolic Expressions Miltiadis Allamanis Pankajan Chanthirasegaran Pushmeet Kohli Charles Sutton CLL NAI 77 99 0 04 Nov 2016
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 323 10,464 0 21 Jul 2016
DeepMath - Deep Sequence Models for Premise Selection Alexander A. Alemi François Chollet N. Eén G. Irving Christian Szegedy Josef Urban LRM AIMat 46 229 0 14 Jun 2016
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 420 12,680 0 11 Dec 2014
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 613 31,467 0 16 Jan 2013
SATzilla: Portfolio-based Algorithm Selection for SAT Lin Xu Frank Hutter Holger H. Hoos Kevin Leyton-Brown 98 974 0 31 Oct 2011