| Learning Bayesian belief networks: An approach based on the MDL principle W Lam, F Bacchus Computational intelligence 10 (3), 269-293, 1994 | 1225 | 1994 |
| Using temporal logics to express search control knowledge for planning F Bacchus, F Kabanza Artificial intelligence 116 (1-2), 123-191, 2000 | 847 | 2000 |
| Representing and reasoning with probabilistic knowledge. FI Bacchus | 697 | 1989 |
| Planning for temporally extended goals F Bacchus, F Kabanza Annals of Mathematics and Artificial Intelligence 22 (1), 5-27, 1998 | 428 | 1998 |
| From statistical knowledge bases to degrees of belief F Bacchus, AJ Grove, JY Halpern, D Koller Artificial intelligence 87 (1-2), 75-143, 1996 | 383 | 1996 |
| Combining Component Caching and Clause Learning for Effective Model Counting. T Sang, F Bacchus, P Beame, HA Kautz, T Pitassi SAT 4, 7th, 2004 | 341 | 2004 |
| Graphical models for preference and utility F Bacchus, AJ Grove arXiv preprint arXiv:1302.4928, 2013 | 320 | 2013 |
| A Knowledge-Based Approach to Planning with Incomplete Information and Sensing. RPA Petrick, F Bacchus AIPS 2, 212-22, 2002 | 318 | 2002 |
| UCP-networks: A directed graphical representation of conditional utilities C Boutilier, F Bacchus, RI Brafman arXiv preprint arXiv:1301.2259, 2013 | 285 | 2013 |
| On the conversion between non-binary and binary constraint satisfaction problems F Bacchus, P Van Beek AAAI/IAAI, 310-318, 1998 | 262 | 1998 |
| Solving MAXSAT by solving a sequence of simpler SAT instances J Davies, F Bacchus International conference on principles and practice of constraint …, 2011 | 251 | 2011 |
| AIPS 2000 planning competition: The fifth international conference on artificial intelligence planning and scheduling systems F Bacchus Ai magazine 22 (3), 47-47, 2001 | 249 | 2001 |
| Reasoning about noisy sensors and effectors in the situation calculus F Bacchus, JY Halpern, HJ Levesque Artificial Intelligence 111 (1-2), 171-208, 1999 | 248 | 1999 |
| Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing. RPA Petrick, F Bacchus ICAPS, 2-11, 2004 | 230 | 2004 |
| A heuristic search approach to planning with temporally extended preferences JA Baier, F Bacchus, SA McIlraith Artificial Intelligence 173 (5-6), 593-618, 2009 | 216 | 2009 |
| Algorithms and complexity results for# SAT and Bayesian inference F Bacchus, S Dalmao, T Pitassi 44th Annual IEEE Symposium on Foundations of Computer Science, 2003 …, 2003 | 216 | 2003 |
| Maximum satisfiability using core-guided MaxSAT resolution N Narodytska, F Bacchus Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 213 | 2014 |
| Effective preprocessing with hyper-resolution and equality reduction F Bacchus, J Winter International conference on theory and applications of satisfiability …, 2003 | 206 | 2003 |
| Downward refinement and the efficiency of hierarchical problem solving F Bacchus, Q Yang Artificial Intelligence 71 (1), 43-100, 1994 | 200 | 1994 |
| Rewarding behaviors F Bacchus, C Boutilier, A Grove Proceedings of the National Conference on Artificial Intelligence, 1160-1167, 1996 | 191 | 1996 |
