| Year |
Citation |
Score |
| 2015 |
Lonsing F, Bacchus F, Biere A, Egly U, Seidl M. Enhancing search-based QBF solving by dynamic blocked clause elimination Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9450: 418-433. DOI: 10.1007/978-3-662-48899-7_29 |
0.371 |
|
| 2014 |
Narodytska N, Legg A, Bacchus F, Ryzhyk L, Walker A. Solving games without controllable predecessor Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8559: 533-540. DOI: 10.1007/978-3-319-08867-9_35 |
0.357 |
|
| 2014 |
Bacchus F, Davies J, Tsimpoukell M, Katsirelos G. Relaxation search: A simple way of managing optional clauses Proceedings of the National Conference On Artificial Intelligence. 2: 835-841. |
0.353 |
|
| 2014 |
Narodytska N, Bacchus F. Maximum satisfiability using core-guided MaxSat resolution Proceedings of the National Conference On Artificial Intelligence. 4: 2717-2723. |
0.339 |
|
| 2013 |
Davies J, Bacchus F. Postponing optimization to speed up MAXSAT solving Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8124: 247-262. DOI: 10.1007/978-3-642-40627-0_21 |
0.322 |
|
| 2013 |
Goultiaeva A, Bacchus F. Recovering and utilizing partial duality in QBF Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7962: 83-99. DOI: 10.1007/978-3-642-39071-5_8 |
0.735 |
|
| 2013 |
Davies J, Bacchus F. Exploiting the power of MIP solvers in MAXSAT Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7962: 166-181. DOI: 10.1007/978-3-642-39071-5_13 |
0.318 |
|
| 2012 |
Goultiaeva A, Bacchus F. Off the trail: Re-examining the CDCL algorithm Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7317: 30-43. DOI: 10.1007/978-3-642-31612-8_4 |
0.7 |
|
| 2012 |
Zhang L, Bacchus F. MAXSAT heuristics for cost optimal planning Proceedings of the National Conference On Artificial Intelligence. 3: 1846-1852. |
0.311 |
|
| 2011 |
Goultiaeva A, Van Gelder A, Bacchus F. A uniform approach for generating proofs and strategies for both true and false QBF formulas Ijcai International Joint Conference On Artificial Intelligence. 546-553. DOI: 10.5591/978-1-57735-516-8/IJCAI11-099 |
0.736 |
|
| 2011 |
Davies J, Bacchus F. Solving MAXSAT by solving a sequence of simpler SAT instances Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6876: 225-239. DOI: 10.1007/978-3-642-23786-7_19 |
0.406 |
|
| 2010 |
Davies J, Cho J, Bacchus F. Using learnt clauses in MAXSAT Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6308: 176-190. DOI: 10.1007/978-3-642-15396-9_17 |
0.381 |
|
| 2010 |
Goultiaeva A, Bacchus F. Exploiting circuit representations in QBF solving Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6175: 333-339. DOI: 10.1007/978-3-642-14186-7_29 |
0.745 |
|
| 2010 |
Mangassarian H, Le B, Goultiaeva A, Veneris A, Bacchus F. Leveraging dominators for preprocessing QBF Proceedings -Design, Automation and Test in Europe, Date. 1695-1700. |
0.741 |
|
| 2010 |
Goultiaeva A, Bacchus F. Exploiting QBF duality on a circuit representation Proceedings of the National Conference On Artificial Intelligence. 1: 71-76. |
0.738 |
|
| 2009 |
Bacchus F, Dalmao S, Pitassi T. Solving #Sat and bayesian inference with backtracking search Journal of Artificial Intelligence Research. 34: 391-442. DOI: 10.1613/Jair.2648 |
0.493 |
|
| 2009 |
Goultiaeva A, Iverson V, Bacchus F. Beyond CNF: A circuit-based QBF solver Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5584: 412-426. DOI: 10.1007/978-3-642-02777-2_38 |
0.766 |
|
| 2009 |
Kitching M, Bacchus F. Set branching in constraint optimization Ijcai International Joint Conference On Artificial Intelligence. 532-537. |
0.302 |
|
| 2009 |
Kitching M, Bacchus F. Exploiting decomposition on constraint problems with high tree-width Ijcai International Joint Conference On Artificial Intelligence. 525-531. |
0.313 |
|
| 2008 |
Kitching M, Bacchus F. Exploiting decomposition in constraint optimization problems Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5202: 478-492. DOI: 10.1007/978-3-540-85958-1_32 |
0.41 |
|
| 2007 |
Baier JA, Bacchus F, McIlraith SA. A heuristic search approach to planning with temporally extended preferences Ijcai International Joint Conference On Artificial Intelligence. 1808-1815. DOI: 10.1016/J.Artint.2008.11.011 |
0.371 |
|
| 2007 |
Bacchus F. Caching in backtracking search Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4741: 1. |
0.345 |
|
| 2007 |
Kitching M, Bacchus F. Symmetric component caching Ijcai International Joint Conference On Artificial Intelligence. 118-124. |
0.378 |
|
| 2007 |
Bacchus F. GAC via unit propagation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4741: 133-147. |
0.315 |
|
| 2007 |
Davies J, Bacchus F. Using more reasoning to improve #SAT solving Proceedings of the National Conference On Artificial Intelligence. 1: 185-190. |
0.33 |
|
| 2007 |
Samulowitz H, Bacchus F. Dynamically partitioning for solving QBF Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4501: 215-229. |
0.385 |
|
| 2007 |
Bacchus F, Stergiou K. Solution directed backjumping for QCSP Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4741: 148-163. |
0.355 |
|
| 2006 |
Samulowitz H, Davies J, Bacchus F. Preprocessing QBF Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4204: 514-529. |
0.402 |
|
| 2006 |
Samulowitz H, Bacchus F. Binary clause reasoning in QBF Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4121: 353-367. |
0.334 |
|
| 2005 |
Samulowitz H, Bacchus F. Using SAT in QBF Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3709: 578-592. DOI: 10.1007/11564751_43 |
0.411 |
|
| 2004 |
Thiffault C, Bacchus F, Walsh T. Solving non-clausal formulas with DPLL search Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3258: 663-678. |
0.405 |
|
| 2004 |
Bacchus F, Winter J. Effective preprocessing with hyper-resolution and equality reduction Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2919: 341-355. |
0.427 |
|
| 2003 |
Bacchus F, Dalmao S, Pitassi T. Algorithms and complexity results for #SAT and Bayesian inference Proceedings - Annual Ieee Symposium On Foundations of Computer Science, Focs. 2003: 340-351. DOI: 10.1109/SFCS.2003.1238208 |
0.322 |
|
| 2002 |
Bacchus F, Chen X, Van Beek P, Walsh T. Binary vs. non-binary constraints Artificial Intelligence. 140: 1-37. DOI: 10.1016/S0004-3702(02)00210-2 |
0.391 |
|
| 2002 |
Bacchus F. Enhancing Davis Putnam with extended binary clause reasoning Proceedings of the National Conference On Artificial Intelligence. 613-619. |
0.398 |
|
| 2000 |
Bacchus F, Kabanza F. Using temporal logics to express search control knowledge for planning Artificial Intelligence. 116: 123-191. DOI: 10.1016/S0004-3702(99)00071-5 |
0.306 |
|
| 1998 |
Bacchus F, Kabanza F. Planning for temporally extended goals Annals of Mathematics and Artificial Intelligence. 22: 5-27. DOI: 10.1023/A:1018985923441 |
0.337 |
|
| 1996 |
Bacchus F, Grove AJ, Halpern JY, Koller D. From statistical knowledge bases to degrees of belief Artificial Intelligence. 87: 75-143. DOI: 10.1016/S0004-3702(96)00003-3 |
0.385 |
|
| 1995 |
Bacchus F, Grove A. On the forward checking algorithm Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 976: 292-309. DOI: 10.1007/3-540-60299-2_18 |
0.319 |
|
| 1995 |
Bacchus F, Van Run P. Dynamic variable ordering in CSPs Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 976: 258-275. DOI: 10.1007/3-540-60299-2_16 |
0.314 |
|
| 1994 |
Bacchus F, Yang Q. Downward refinement and the efficiency of hierarchical problem solving Artificial Intelligence. 71: 43-100. DOI: 10.1016/0004-3702(94)90062-0 |
0.432 |
|
| 1991 |
Bacchus F. Representing and reasoning with probabilistic knowledge: a logical approach to probabilities American Journal of Psychology. 105: 498. DOI: 10.2307/1423204 |
0.376 |
|
| 1991 |
Bacchus F, Tenenberg J, Koomen JA. A non-reified temporal logic Artificial Intelligence. 52: 87-108. DOI: 10.1016/0004-3702(91)90025-F |
0.317 |
|
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