Fahiem Bacchus
Papers available on-line
Bayesian Inference and #SAT
-
Using More Reasoning to Improve
#SAT Solving, J. Davies and F. Bacchus,
National Conference on Artificial Intelligence
(AAAI-07) ,
pages 185-190, 2007.
-
Algorithms and Complexity Results
for #Sat and Bayesian Inference,
F. Bacchus, S. Dalmao, and T. Pitassi FOCS 2003
340-351, 2003.
-
Combining Component Caching and Clause
Learning for Effective Model Counting, T. Sang, F. Bacchus, P. Beame,
H. Kautz, and T. Pitassi, presented at SAT 2004 9 pages.
-
Value Elimination: Bayesian
Inference via Backtracking Search,
F. Bacchus, S. Dalmao, and T. Pitassi Uncertainty in Artificial
Intelligence (UAI-2003) 20-28, 2003.
Planning
-
A Heuristic Search
Approach to Planning with Temporally Extended Preferences,
J. A. Baier, F. Bacchus and S. McIlraith, International Joint
Conference on Artificial Intelligence (IJCAI-07) pages 1808--1815, 2007.
-
Extending the
Knowledge-Based approach to Planning with Incomplete Information and
Sensing, R. Petrick and F. Bacchus, International Conference on
Automated Planning and Scheduling
(ICAPS2004) pages 2-11, 2004.
-
Utilizing Structured
Representations and CSPs in Conformant Probabilistic Planning, N. Hyafil and F. Bacchus,
European Conference on Artificial Intelligence 2004. pages 1033-1034 (link
points to a more comprehensible version).
-
The Power of Modeling---a Response to PDDL2.1,
F. Bacchus Journal of Artificial Intelligence Research (JAIR)
Volume 20 pages 125-132, 2003.
-
Generalizing GraphPlan by Formulating Planning as a CSP,
A. Lopez and F. Bacchus International Joint Conference on
Artificial Intelligence IJCAI-2003, pages 954-960, 2003.
-
Conformant Probabilistic
Planning via CSPs, N. Hyafil and F. Bacchus
International Conference on Automated Planning and Scheduling
(ICAPS-2003), pages 205-214, 2003.
-
A Knowledge-Based Approach to
Planning with Incomplete Information and Sensing,
R. Petrick and F. Bacchus AI Planning and Scheduling
(AIPS2002) pages 212-222, 2002.
-
Planning with Resources and Concurrency:
A Forward Chaining Approach,
F. Bacchus and M. Ady, International Joint Conference on Artificial Intelligence (IJCAI-2001), pages 417-424, 2001.
-
Inner and Outer Boundaries of Literals: A Mechanism for Computing Domain Specific Information,
F. Bacchus and Cameron Bruce Fraser, AIPS-2000 Workshop on Analysing and Exploiting Domain Knowledge for Efficient Planning. 2000.
-
Evaluating
First Order Formulas---the foundation for a general Search Engine,
F. Bacchus and M. Ady, unpublished manuscript 1999.
-
Precondition
Control, F. Bacchus and M. Ady, unpublished manuscript
1999.
-
Using
Temporal Logics to Express Search Control Knowledge for Planning,
F. Bacchus and F. Kabanza, Artificial Intelligence volume 16, pages 123--191, 2000.
- Making
Forward Chaining Relevant, F. Bacchus and Y. W. Teh, Artificial
Intelligence Planning Systems (AIPS-98), pages 54-61, 1998.
- Modeling an
Agent's Incomplete Knowledge during Planning and Execution, F.
Bacchus and R. Petrick, Knowledge Represention and Reasoning, pages
432--443. 1998.
- Planning for
Temporally Extended Goals, F. Bacchus and F. Kabanza, Annals of
Mathematics and Artificial Intelligence, vol. 22, pages 5--27, 1998.
- Reasoning about
Noisy Sensors and Effectors in the Situation Calculus, F. Bacchus,
J. Y. Halpern, and H. J. Levesque, Artificial Intelligence vol 111,
pages 171-208, 1999..
- Structured
Solution Methods for Non-Markovian Decision Processes, F. Bacchus,
C. Boutilier and A. Grove, National Conference on Artpificial
Intelligence (AAAI-97), pages 112--117, 1997.
- Rewarding
Behaviors, F. Bacchus, C. Boutilier and A. Grove, National
Conference on Artificial Intelligence (AAAI-96), pages 1160--1167,
1996.
- Planning for
Temporally Extended Goals, F. Bacchus and F. Kabanza, National
Conference on Artificial Intelligence (AAAI-96), pages 1215--1222,
1996.
- Using
Temporal Logic to Control Search in a Forward Chaining Planner, F.
Bacchus and F. Kabanza, New Directions in Planning, M. Ghallab and A.
Milani (Eds.) IOS Press, pages 141--153, 1996.
- Reasoning
about Noisy Sensors in the Situation Calculus, F. Bacchus, J.Y.
Halpern and H.J. Levesque, International Joint Conference on Artificial
Intelligence (IJCAI-95), pages 1933--1940, 1995.
- Downward
Refinement and the Efficiency of Hierarchical Problem Solving, F.
Bacchus and Q. Yang, Artificial Intelligence vol. 71, pages
43--100, 1994.
- The Expected
Value of Hierarchical Problem Solving, F. Bacchus and Q. Yang, National
Conference on Artificial Intelligence (AAAI-92), pages 364--374, 1992.
Constraint Satisfaction and SAT
-
Solution Directed Backjumping for
QCSP, F. Bacchus and K. Stergiou,
International Conference on Principles and Practice of Constraint
Programming (CP 2007) , pages 148-163, 2007.
-
GAC via Unit Propagation, F. Bacchus,
International Conference on Principles and Practice of Constraint
Programming (CP 2007) , pages 133-147, 2007.
-
Using
Expectation Maximization to Find Likely Assignments for Solving
CSP's, E. Hsu, M. Kitching, F. Bacchus and
S. McIlraith,
National Conference on Artificial Intelligence
(AAAI-07) , pages 224-230, 2007.
-
Symmetric Component Caching,
M. Kitching and F. Bacchus,
International Joint Conference on Artificial Intelligence
(IJCAI-07) , pages 118--124, 2007.
-
Dynamically Partitioning for Solving QBF, H. Samulowitz and F.
Bacchus, Theory and Applications of Satisfiability Testing
(SAT 2007), pages 215-229, 2007.
-
Preprocessing QBF,
H. Samulowitz, J. Davies and F. Bacchus, International Conference on Principles and Practice of Constraint
Programming (CP 2006), pages 514--529, 2006.
-
Binary Clause Reasoning in QBF,
H. Samulowitz and F. Bacchus, Theory and Applications of
Satisfiability Testing (SAT 2006), pages 353-367, 2006.
-
Using SAT in QBF, H. Samulowitz and F.
Bacchus, International Conference on Principles and Practice of
Constraint Programming (CP-2005), pages 578-592, 2005.
-
Propagating Logical Combinations of Constraints,
F. Bacchus and T. Walsh, International Joint Conference on Artificial
Intelligence (IJCAI-2005), pages 35--40.
-
Generalized NoGoods in CSPs, G.
Katsirelos and F. Bacchus, National Conference on Artificial
Intelligence (AAAI-2005) pages 390-396, 2005.
-
Solving Non-clausal Formulas with DPLL
search, C. Thiffault, F. Bacchus, and T. Walsh, Principles and
Practice of Constraint Programming--CP 2004 pages 663--678, 2004.
-
Unrestricted Nogood Recording in
CSP Search, G. Katsirelos and F. Bacchus, Principles and Practice of
Constraint Programming--CP 2003 pages 873-877, 2003.
- Effective Preprocessing with
Hyper-Resolution and Equality Reduction, F. Bacchus and
J. Winter, In Sat 2003 Lecture Notes in Computer Science
2919, pages 341-355
-
Enhancing Davis Putnam with Extended
Binary Clause Reasoning,
F. Bacchus, National Conference on Artificial
Intelligence (AAAI-2002) pages 613-619, 2002.
-
Exploring the Computational Tradeoff
of more Reasoning and Less Searching,
F. Bacchus, Fifth International Symposium on Theory and
Applications of Satisfiability Testing, pages 7-16, 2002.
-
Binary vs. Non-Binary Constraints,
F. Bacchus, X. Chen, P. van Beek, and T. Walsh, Artificial
Intelligence vol 140, 1-37, 2002
-
GAC on Conjunctions of Constraints,
G. Katsirelos and F. Bacchus, Principles and Practice of Constraint
Programming--CP 2001 pages 610-614, 2001.
-
Extending Forward Checking,
F. Bacchus, Principles and Practice of Constraint
Programming--CP 2000, pages 35-51, 2000.
-
A Uniform View of
Backtracking,
F. Bacchus, unpublished manuscript 2000.
- Looking
Forward in Constraint Satisfaction Algorithms, F. Bacchus and A.
Grove, unpublished manuscript, 1999.
- On the
Conversion between Non-Binary and Binary Constraint Satisfaction Problems,
F. Bacchus and P. van Beek, National Conference on Artificial
Intelligence (AAAI-98), pages 311-318, 1998.
- On the Forward
Checking Algorithm, F. Bacchus and A. Grove, Principles and
Practice of Constraint Programming (CP-95), pages 292--309, 1995. Lecture
Notes in Computer Science #976, Springer Verlag
- Dynamic
Variable Ordering in CSPs, F. Bacchus and P. van Run, Principles
and Practice of Constraint Programming (CP-95), pages 258--275, 1995. Lecture
Notes in Computer Science #976, Springer Verlag.
- Domain
Independent Heuristics in Hybrid Algorithms for CSPs, P. van Run,
MMath thesis 1994 (under my supervision), Department of Computer Science,
University of Waterloo, Waterloo, Ontario, Canada.
- Algorithms for
Constraint Satisfaction Problems (CSPs), Z. Liu, MMath thesis 1998
(under my supervision), Department of Computer Science, University of
Waterloo, Waterloo, Ontario, Canada.
Logics for Probabilities/Non-Monotonic Reasoning
- From
Statistical Knowledge Bases to Degrees of Belief, F. Bacchus, A.
Grove, J.Y. Halpern, and D. Koller, Artificial Intelligence, vol.
87, pages 75--143, 1996.
- Forming
Beliefs about a Changing World, F. Bacchus, A. Grove, J. Y.
Halpern, and D. Koller, National Conference on Artificial Intelligence
(AAAI-94), pages 222-229, 1994.
- Generating
New Beliefs from Old, F. Bacchus, A. Grove, J. Y. Halpern, and D.
Koller, Uncertainty in Artificial Intelligence (UAI-94), pages
37--45, 1994.
- Statistical
Foundations for Default Reasoning, F. Bacchus, A. Grove, J. Y.
Halpern, and D. Koller, International Joint Conference on Artificial
Intelligence (IJCAI-93), pages 563--569, 1993.
- From
Statistics to Beliefs, F. Bacchus, A. Grove, J. Y. Halpern, and D.
Koller, National Conference on Artificial Intelligence (AAAI-92),
pages 602--608, 1992.
- Default Reasoning From Statistics,,
F. Bacchus, National Conference on Artificial Intelligence (AAAI-91),
pages 392--398, 1991.
- LP---A Logic
for Representing and Reasoning with Statistical Knowledge, F.
Bacchus, Computational Intelligence, vol 6, pages 209--231, 1990.
- Probabilistic
Belief Logics, F. Bacchus, Proceedings of European Conference
on Artificial Intelligence (ECAI-90), pages 59--64, 1990.
- A Modest,
but Semantically Well Founded, Inheritance Reasoner, F. Bacchus, Proceedings
of International Joint Conference on AI (IJCAI-89), pages 1104--1109,
1989.
- Representing
and Reasoning with Probabilistic Knowledge, M.I.T. Press,
1990.
Utility Theory
-
UCP-Networks: A Directed Graphical
Representation of Conditional Utilities, C. Boutilier,
F. Bacchus and R. Brafman Uncertainty
in Artificial Intelligence (UAI-2001))pages 56--64 2001.
-
Independence and Qualitative Decision Theory,
F. Bacchus and A. GroveAAAI Spring Symposium on Qualitative
preferences in deliberation and practical reasoning)1997.
- Utility Independence
in a Qualitative Decision Theory, F. Bacchus and A. Grove, Principles
of Knowledge Representation and Reasoning (KR-96), pages 542--552,
1996.
- Graphical
models for preference and utility, F. Bacchus and
A. Grove,
Uncertainty
in Artificial Intelligence (UAI-95), pages 3--10, 1995.
Learning Bayes Nets
- Using New
Data to Refine a Bayesian Network, W. Lam and F. Bacchus, Uncertainty
in Artificial Intelligence (UAI-94), pages 383--390, 1994.
- Learning
Bayesian Belief Networks: An Approach based on the MDL Principle,
W. Lam and F. Bacchus, Computational Intelligence, vol. 10, pages
269--293, 1994.
- Using Causal
Information and Local Measures to Learn Bayesian Networks, W. Lam
and F. Bacchus Uncertainty in Artificial Intelligence (UAI-93),
pages 243--250, 1993.
- Using
First-Order Probability Logics for the Construction of Bayesian Networks,
F. Bacchus, Uncertainty in Artificial Intelligence (UAI-94), pages
219--226, 1993.
- Learning
Bayesian Belief Networks, W. Lam and F. Bacchus, Pacific Rim
Conference on Artificial Intelligence (PRICAI-92), pages 1237--1243,
1992.
Knowledge Representation/Philosophy
- A
Non-Reified Temporal Logic, F. Bacchus, J. Tenenberg, and J.
Koomen, Artificial Intelligence, vol 52, pages 87--108, 1991.
- Against
Conditionalization, F. Bacchus, H. Kyburg, and M. Thalos, Synthese,
vol 85, pages 475--506, 1990.
Back to my home page.