Fahiem Bacchus
Fahiem Bacchus
Professor of Computer Science, University of Toronto
Verified email at cs.toronto.edu - Homepage
Cited by
Cited by
Learning Bayesian belief networks: An approach based on the MDL principle
W Lam, F Bacchus
Computational intelligence 10 (3), 269-293, 1994
Using temporal logics to express search control knowledge for planning
F Bacchus, F Kabanza
Artificial intelligence 116 (1-2), 123-191, 2000
Representing and reasoning with probabilistic knowledge.
FI Bacchus
Planning for temporally extended goals
F Bacchus, F Kabanza
Annals of Mathematics and Artificial Intelligence 22 (1-2), 5-27, 1998
Graphical models for preference and utility
F Bacchus, AJ Grove
arXiv preprint arXiv:1302.4928, 2013
A Knowledge-Based Approach to Planning with Incomplete Information and Sensing.
RPA Petrick, F Bacchus
AIPS, 212-222, 2002
From statistical knowledge bases to degrees of belief
F Bacchus, AJ Grove, JY Halpern, D Koller
Artificial intelligence 87 (1-2), 75-143, 1996
UCP-networks: A directed graphical representation of conditional utilities
C Boutilier, F Bacchus, RI Brafman
arXiv preprint arXiv:1301.2259, 2013
Combining Component Caching and Clause Learning for Effective Model Counting.
T Sang, F Bacchus, P Beame, HA Kautz, T Pitassi
SAT 4, 7th, 2004
On the conversion between non-binary and binary constraint satisfaction problems
F Bacchus, P Van Beek
AAAI/IAAI, 310-318, 1998
Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing.
RPA Petrick, F Bacchus
ICAPS, 2-11, 2004
AIPS 2000 planning competition: The fifth international conference on artificial intelligence planning and scheduling systems
F Bacchus
Ai magazine 22 (3), 47-47, 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
Effective preprocessing with hyper-resolution and equality reduction
F Bacchus, J Winter
International conference on theory and applications of satisfiability …, 2003
Using temporal logic to control search in a forward chaining planner
F Bacchus, F Kabanza
Proceedings of the 3rd European Workshop on Planning, 141-153, 1995
Downward refinement and the efficiency of hierarchical problem solving
F Bacchus, Q Yang
Artificial Intelligence 71 (1), 43-100, 1994
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
Dynamic variable ordering in CSPs
F Bacchus, P Van Run
International Conference on Principles and Practice of Constraint …, 1995
A heuristic search approach to planning with temporally extended preferences
JA Baier, F Bacchus, SA McIlraith
Artificial Intelligence 173 (5-6), 593-618, 2009
Solving MAXSAT by solving a sequence of simpler SAT instances
J Davies, F Bacchus
International conference on principles and practice of constraint …, 2011
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