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BibBase bacchus, f
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  2012 (2)
MAXSAT Heuristics for Cost Optimal Planning. Zhang, L.; and Bacchus, F. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI-2012), 2012.
MAXSAT Heuristics for Cost Optimal Planning [pdf]Paper   link   bibtex  
Off the Trail: Re-examining the CDCL Algorithm. Goultiaeva, A.; and Bacchus, F. In Proceedings of the 15th International Conference on Theory and Applications of Satisfiability Testing (SAT-2012), pages 30-43, 2012.
Off the Trail: Re-examining the CDCL Algorithm [pdf]Paper   Off the Trail: Re-examining the CDCL Algorithm [link]Link   link   bibtex  
  2011 (3)
Proceedings of the 21st International Conference on Automated Planning and Scheduling, ICAPS 2011, Freiburg, Germany June 11-16, 2011. Bacchus, F.; Domshlak, C.; Edelkamp, S.; and Helmert, M., editors. In Bacchus, F.; Domshlak, C.; Edelkamp, S.; and Helmert, M., editor(s), 2011. AAAI
Proceedings of the 21st International Conference on Automated Planning and Scheduling, ICAPS 2011, Freiburg, Germany June 11-16, 2011 [link]Paper   link   bibtex  
A Uniform Approach for Generating Proofs and Strategies for Both True and False QBF Formulas. Goultiaeva, A.; Gelder, A. V.; and Bacchus, F. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-2011), pages 546-553, 2011.
A Uniform Approach for Generating Proofs and Strategies for Both True and False QBF Formulas [pdf]Paper   link   bibtex  
Solving MAXSAT by Solving a Sequence of Simpler SAT Instances. Davies, J.; and Bacchus, F. In 17th International Conference on Principles and Practice of Constraint Programming (CP-2011), pages 225-239, 2011.
Solving MAXSAT by Solving a Sequence of Simpler SAT Instances [pdf]Paper   Solving MAXSAT by Solving a Sequence of Simpler SAT Instances [link]Link   link   bibtex  
  2010 (4)
Using Learnt Clauses in maxsat. Davies, J.; Cho, J.; and Bacchus, F. In 16th International Conference on Principles and Practice of Constraint Programming (CP-2010), pages 176-190, 2010.
Using Learnt Clauses in maxsat [pdf]Paper   Using Learnt Clauses in maxsat [link]Link   link   bibtex  
Exploiting QBF Duality on a Circuit Representation. Goultiaeva, A.; and Bacchus, F. In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI-2010), pages 71-76, 2010.
Exploiting QBF Duality on a Circuit Representation [pdf]Paper   Exploiting QBF Duality on a Circuit Representation [link]Link   link   bibtex  
Leveraging dominators for preprocessing QBF. Mangassarian, H.; Le, B.; Goultiaeva, A.; Veneris, A. G.; and Bacchus, F. In Design, Automation and Test in Europe (DATE 2010), pages 1695-1700, 2010.
Leveraging dominators for preprocessing QBF [pdf]Paper   Leveraging dominators for preprocessing QBF [link]Link   link   bibtex  
Exploiting Circuit Representations in QBF Solving. Goultiaeva, A.; and Bacchus, F. In Proceedings of the 13th International Conference on Theory and Applications of Satisfiability Testing (SAT-2010), pages 333-339, 2010.
Exploiting Circuit Representations in QBF Solving [link]Link   Exploiting Circuit Representations in QBF Solving [pdf]Paper   link   bibtex  
  2009 (5)
Solving #SAT and Bayesian Inference with Backtracking Search. Bacchus, F.; Dalmao, S.; and Pitassi, T. J. Artif. Intell. Res. (JAIR), 34: 391-442. 2009.
Solving #SAT and Bayesian Inference with Backtracking Search [link]Paper   link   bibtex  
A heuristic search approach to planning with temporally extended preferences. Baier, J. A.; Bacchus, F.; and McIlraith, S. A. , 173(5–6): 593-618. 2009.
A heuristic search approach to planning with temporally extended preferences [link]Paper   link   bibtex  
Exploiting Decomposition on Constraint Problems with High Tree-Width. Kitching, M.; and Bacchus, F. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-2009), pages 525-531, 2009.
Exploiting Decomposition on Constraint Problems with High Tree-Width [pdf]Paper   link   bibtex  
Set Branching in Constraint Optimization. Kitching, M.; and Bacchus, F. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-2009), pages 532-537, 2009.
Set Branching in Constraint Optimization [pdf]Paper   link   bibtex  
Beyond CNF: A Circuit-Based QBF Solver. Goultiaeva, A.; Iverson, V.; and Bacchus, F. In Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing (SAT-2009), pages 412-426, 2009.
Beyond CNF: A Circuit-Based QBF Solver [pdf]Paper   Beyond CNF: A Circuit-Based QBF Solver [link]Link   link   bibtex  
  2008 (3)
Clause Learning Can Effectively P-Simulate General Propositional Resolution. Hertel, P.; Bacchus, F.; Pitassi, T.; and Gelder, A. V. In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-2008), pages 283-290, 2008.
Clause Learning Can Effectively P-Simulate General Propositional Resolution [pdf]Paper   link   bibtex  
Exploiting Decomposition in Constraint Optimization Problems. Kitching, M.; and Bacchus, F. In Proceedings of the 14th International Conference on Principles and Practice of Constraint Programming (CP-2008), pages 478-492, 2008.
Exploiting Decomposition in Constraint Optimization Problems [pdf]Paper   Exploiting Decomposition in Constraint Optimization Problems [link]Link   link   bibtex  
Distributional Importance Sampling for Approximate Weighted Model Counting. Davies, J.; and Bacchus, F. In Workshop on Counting Problems in CSP and SAT, and other neighbouring problems, 2008.
Distributional Importance Sampling for Approximate Weighted Model Counting [pdf]Paper   link   bibtex  
  2007 (8)
Using More Reasoning to Improve #SAT Solving. Davies, J.; and Bacchus, F. In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-2007), pages 185-190, 2007.
Using More Reasoning to Improve #SAT Solving [pdf]Paper   link   bibtex  
Using Expectation Maximization to Find Likely Assignments for Solving CSP's. Hsu, E. I.; Kitching, M.; Bacchus, F.; and McIlraith, S. A. In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-2007), pages 224-230, 2007.
Using Expectation Maximization to Find Likely Assignments for Solving CSP's [pdf]Paper   link   bibtex  
Caching in Backtracking Search (Invited Talk). Bacchus, F. In Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming (CP-2007), pages 1-1, 2007.
Caching in Backtracking Search (Invited Talk) [ppt]Paper   Caching in Backtracking Search (Invited Talk) [link]Link   link   bibtex  
GAC Via Unit Propagation. Bacchus, F. In Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming (CP-2007), pages 133-147, 2007.
GAC Via Unit Propagation [pdf]Paper   GAC Via Unit Propagation [link]Link   link   bibtex  
Solution Directed Backjumping for QCSP. Bacchus, F.; and Stergiou, K. In Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming (CP-2007), pages 148-163, 2007.
Solution Directed Backjumping for QCSP [pdf]Paper   Solution Directed Backjumping for QCSP [link]Link   link   bibtex  
Symmetric Component Caching. Kitching, M.; and Bacchus, F. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-2007), pages 118-124, 2007.
Symmetric Component Caching [pdf]Paper   Symmetric Component Caching [pdf]Link   link   bibtex  
A Heuristic Search Approach to Planning with Temporally Extended Preferences. Baier, J. A.; Bacchus, F.; and McIlraith, S. A. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-2007), pages 1808-1815, 2007.
A Heuristic Search Approach to Planning with Temporally Extended Preferences [pdf]Paper   A Heuristic Search Approach to Planning with Temporally Extended Preferences [pdf]Link   link   bibtex  
Dynamically Partitioning for Solving QBF. Samulowitz, H.; and Bacchus, F. In Proceedings of the 10th International Conference on Theory and Applications of Satisfiability Testing (SAT-2007), pages 215-229, 2007.
Dynamically Partitioning for Solving QBF [pdf]Paper   Dynamically Partitioning for Solving QBF [link]Link   link   bibtex  
  2006 (3)
Preprocessing QBF. Samulowitz, H.; Davies, J.; and Bacchus, F. In Proceedings of the 12th International Conference on Principles and Practice of Constraint Programming (CP-2006), pages 514-529, 2006.
Preprocessing QBF [pdf]Paper   Preprocessing QBF [link]Link   link   bibtex  
CSPs: Adding Structure to SAT (Invited Talk). Bacchus, F. In Proceedings of the 9th International Conference on Theory and Applications of Satisfiability Testing (SAT-2006), pages 10-10, 2006.
CSPs: Adding Structure to SAT (Invited Talk) [ppt]Paper   CSPs: Adding Structure to SAT (Invited Talk) [link]Link   link   bibtex  
Binary Clause Reasoning in QBF. Samulowitz, H.; and Bacchus, F. In Proceedings of the 9th International Conference on Theory and Applications of Satisfiability Testing (SAT-2006), pages 353-367, 2006.
Binary Clause Reasoning in QBF [pdf]Paper   Binary Clause Reasoning in QBF [link]Link   link   bibtex  
  2005 (5)
Theory and Applications of Satisfiability Testing, 8th International Conference, SAT 2005, St Andrews, UK, June 19-23, 2005. Bacchus, F.; and Walsh, T., editors. Volume 3569, of Lecture Notes in Computer Science.Springer. 2005.
Theory and Applications of Satisfiability Testing, 8th International Conference, SAT 2005, St Andrews, UK, June 19-23, 2005 [link]Paper   link   bibtex  
21st Conference on Uncertainty in Artificial Intelligence, UAI 2005, Edinburgh, Scotland. Bacchus, F.; and Jaakkola, T., editors. Brightdoc On-Line Demand Publishers. 2005.
21st Conference on Uncertainty in Artificial Intelligence, UAI 2005, Edinburgh, Scotland [link]Paper   link   bibtex  
Generalized NoGoods in CSPs. Katsirelos, G.; and Bacchus, F. In Proceedings of the 20th AAAI Conference on Artificial Intelligence (AAAI-2005), pages 390-396, 2005.
Generalized NoGoods in CSPs [pdf]Paper   link   bibtex  
Using SAT in QBF. Samulowitz, H.; and Bacchus, F. In Proceedings of the 11th International Conference on Principles and Practice of Constraint Programming (CP-2005), pages 578-592, 2005.
Using SAT in QBF [pdf]Paper   Using SAT in QBF [link]Link   link   bibtex  
Propagating Logical Combinations of Constraints. Bacchus, F.; and Walsh, T. In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI-2005), pages 35-40, 2005.
Propagating Logical Combinations of Constraints [pdf]Paper   Propagating Logical Combinations of Constraints [pdf]Link   link   bibtex  
  2004 (5)
Solving Non-clausal Formulas with DPLL Search. Thiffault, C.; Bacchus, F.; and Walsh, T. In Proceedings of the 10th International Conference on Principles and Practice of Constraint Programming (CP-2004), pages 663-678, 2004.
Solving Non-clausal Formulas with DPLL Search [pdf]Paper   Solving Non-clausal Formulas with DPLL Search [link]Link   link   bibtex  
Utilizing Structured Representations and CSP's in Conformant Probabilistic Planning. Hyafil, N.; and Bacchus, F. In Proceedings of the 16th Eureopean Conference on Artificial Intelligence (ECAI-2004), pages 1033-1034, 2004.
Utilizing Structured Representations and CSP's in Conformant Probabilistic Planning [pdf]Paper   link   bibtex  
Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing. Petrick, R. P. A.; and Bacchus, F. In Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS-2004), pages 2-11, 2004.
Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing [pdf]Paper   link   bibtex  
Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing. Petrick, R. P. A.; and Bacchus, F. In Proceedings of the 9th International Conference on Principles of Knowledge Representation and Reasoning (KR-2004), pages 613-622, 2004.
Extending the Knowledge-Based Approach to Planning with Incomplete Information and Sensing [pdf]Paper   link   bibtex  
Combining Component Caching and Clause Learning for Effective Model Counting. Sang, T.; Bacchus, F.; Beame, P.; Kautz, H. A.; and Pitassi, T. In Proceedings of the 7th International Conference on Theory and Applications of Satisfiability Testing (SAT-2004), 2004.
Combining Component Caching and Clause Learning for Effective Model Counting [pdf]Paper   Combining Component Caching and Clause Learning for Effective Model Counting [pdf]Link   link   bibtex  
  2003 (7)
Unrestricted Nogood Recording in CSP Search. Katsirelos, G.; and Bacchus, F. In Proceedings of the 9th International Conference on Principles and Practice of Constraint Programming (CP-2003), pages 873-877, 2003.
Unrestricted Nogood Recording in CSP Search [pdf]Paper   Unrestricted Nogood Recording in CSP Search [link]Link   link   bibtex  
Algorithms and Complexity Results for #SAT and Bayesian Inference. Bacchus, F.; Dalmao, S.; and Pitassi, T. In Proceedings of the 44th Symposium on Foundations of Computer Science (FOCS-2003), pages 340-351, 2003.
Algorithms and Complexity Results for #SAT and Bayesian Inference [pdf]Paper   Algorithms and Complexity Results for #SAT and Bayesian Inference [link]Link   link   bibtex  
Conformant Probabilistic Planning via CSPs. Hyafil, N.; and Bacchus, F. In Proceedings of the 13th International Conference on Automated Planning and Scheduling (ICAPS-2003), pages 205-214, 2003.
Conformant Probabilistic Planning via CSPs [pdf]Paper   link   bibtex  
Generalizing GraphPlan by Formulating Planning as a CSP. Lopez, A.; and Bacchus, F. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI-2003), pages 954-960, 2003.
Generalizing GraphPlan by Formulating Planning as a CSP [pdf]Paper   link   bibtex  
Effective Preprocessing with Hyper-Resolution and Equality Reduction. Bacchus, F.; and Winter, J. In Proceedings of the 6th International Conference on Theory and Applications of Satisfiability Testing (SAT-2003), pages 341-355, 2003.
Effective Preprocessing with Hyper-Resolution and Equality Reduction [pdf]Paper   Effective Preprocessing with Hyper-Resolution and Equality Reduction [link]Link   link   bibtex  
Value Elimination: Bayesian Inference via Backtracking Search. Bacchus, F.; Dalmao, S.; and Pitassi, T. In Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence August (UAI-2003), pages 20-28, 2003.
Value Elimination: Bayesian Inference via Backtracking Search [pdf]Paper   link   bibtex  
The Power of Modeling - a Response to PDDL2.1. Bacchus, F. J. Artif. Intell. Res. (JAIR), 20: 125-132. 2003.
The Power of Modeling - a Response to PDDL2.1 [link]Paper   The Power of Modeling - a Response to PDDL2.1 [link]Link   link   bibtex  
  2002 (3)
Enhancing Davis Putnam with Extended Binary Clause Reasoning. Bacchus, F. In Proceedings of the 18th AAAI Conference on Artificial Intelligence (AAAI-2002), pages 613-619, 2002.
Enhancing Davis Putnam with Extended Binary Clause Reasoning [pdf]Paper   link   bibtex  
A Knowledge-Based Approach to Planning with Incomplete Information and Sensing. Petrick, R. P. A.; and Bacchus, F. In Proceedings of the 6th International Conference on Artificial Intelligence Planning Systems (AIPS-2002), pages 212-222, 2002.
A Knowledge-Based Approach to Planning with Incomplete Information and Sensing [pdf]Paper   link   bibtex  
Binary vs. non-binary constraints. Bacchus, F.; Chen, X.; van Beek, P.; and Walsh, T. Artif. Intell., 140(1/2): 1-37. 2002.
Binary vs. non-binary constraints [link]Paper   link   bibtex  
  2001 (4)
GAC on Conjunctions of Constraints. Katsirelos, G.; and Bacchus, F. In Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming (CP-2001), pages 610-614, 2001.
GAC on Conjunctions of Constraints [pdf]Paper   GAC on Conjunctions of Constraints [link]Link   link   bibtex  
Planning with Resources and Concurrency: A Forward Chaining Approach. Bacchus, F.; and Ady, M. In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI-2001), pages 417-424, 2001.
Planning with Resources and Concurrency: A Forward Chaining Approach [pdf]Paper   link   bibtex  
UCP-Networks: A Directed Graphical Representation of Conditional Utilities. Boutilier, C.; Bacchus, F.; and Brafman, R. I. In Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence (UAI-2001), pages 56-64, 2001.
UCP-Networks: A Directed Graphical Representation of Conditional Utilities [pdf]Paper   UCP-Networks: A Directed Graphical Representation of Conditional Utilities [link]Link   link   bibtex  
The AIPS '00 Planning Competition. Bacchus, F. AI Magazine, 22(3): 47-56. 2001.
The AIPS '00 Planning Competition [link]Paper   link   bibtex  
  2000 (3)
Extending Forward Checking. Bacchus, F. In Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming (CP-2000), pages 35-51, 2000.
Extending Forward Checking [pdf]Paper   Extending Forward Checking [link]Link   link   bibtex  
Using temporal logics to express search control knowledge for planning. Bacchus, F.; and Kabanza, F. Artif. Intell., 116(1-2): 123-191. 2000.
Using temporal logics to express search control knowledge for planning [link]Paper   Using temporal logics to express search control knowledge for planning [link]Link   link   bibtex  
Inner and Outer Boundaries of Literals: A Mechanism for Computing Domain Specific Information. Bacchus, F.; and Fraser, C. B. In AIPS-2000 Workshop on Analysing and Exploiting Domain Knowledge for Efficient Planning, 2000.
Inner and Outer Boundaries of Literals: A Mechanism for Computing Domain Specific Information [pdf]Paper   link   bibtex  
  1999 (3)
Reasoning about Noisy Sensors and Effectors in the Situation Calculus. Bacchus, F.; Halpern, J. Y.; and Levesque, H. J. Artif. Intell., 111(1-2): 171-208. 1999.
Reasoning about Noisy Sensors and Effectors in the Situation Calculus [link]Paper   link   bibtex  
Evaluating First Order Formulas—the foundation for a general Search Engine. Bacchus, F.; and Ady, M. 1999.
Evaluating First Order Formulas—the foundation for a general Search Engine [pdf]Paper   link   bibtex  
Precondition Control. Bacchus, F.; and Ady, M. 1999.
Precondition Control [pdf]Paper   link   bibtex  
  1998 (4)
On the Conversion between Non-Binary and Binary Constraint Satisfaction Problems. Bacchus, F.; and van Beek, P. In Proceedings of the 15th AAAI Conference on Artificial Intelligence (AAAI-1998), pages 310-318, 1998.
On the Conversion between Non-Binary and Binary Constraint Satisfaction Problems [pdf]Paper   link   bibtex  
Making Forward Chaining Relevant. Bacchus, F.; and Teh, Y. W. In Proceedings of the 2nd International Conference on Artificial Intelligence Planning Systems (AIPS-1998), pages 54-61, 1998.
Making Forward Chaining Relevant [pdf]Paper   link   bibtex  
Modeling an Agent's Incomplete Knowledge During Planning and During Execution. Bacchus, F.; and Petrick, R. P. A. In Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR-1998), pages 432-443, 1998.
Modeling an Agent's Incomplete Knowledge During Planning and During Execution [pdf]Paper   link   bibtex  
Planning for Temporally Extended Goals. Bacchus, F.; and Kabanza, F. Ann. Math. Artif. Intell., 22(1-2): 5-27. 1998.
Planning for Temporally Extended Goals [pdf]Paper   link   bibtex  
  1997 (1)
Structured Solution Methods for Non-Markovian Decision Processes. Bacchus, F.; Boutilier, C.; and Grove, A. J. In Proceedings of the 14th AAAI Conference on Artificial Intelligence (AAAI-1997), pages 112-117, 1997.
Structured Solution Methods for Non-Markovian Decision Processes [pdf]Paper   link   bibtex  
  1996 (5)
Rewarding Behaviors. Bacchus, F.; Boutilier, C.; and Grove, A. J. In Proceedings of the 13th AAAI Conference on Artificial Intelligence (AAAI-1996), pages 1160-1167, 1996.
Rewarding Behaviors [pdf]Paper   link   bibtex  
Planning for Temporally Extended Goals. Bacchus, F.; and Kabanza, F. In Proceedings of the 13th AAAI Conference on Artificial Intelligence (AAAI-1996), pages 1215-1222, 1996.
Planning for Temporally Extended Goals [pdf]Paper   link   bibtex  
Utility Independence in a Qualitative Decision Theory. Bacchus, F.; and Grove, A. J. In Proceedings of the 5th International Conference on Principles of Knowledge Representation and Reasoning (KR-1996), pages 542-552, 1996.
Utility Independence in a Qualitative Decision Theory [pdf]Paper   link   bibtex  
Using Temporal Logics for Planning and Control. Bacchus, F. In Proceedings of the 3rd International Workshop on Temporal Representation and Reasoning (TIME-1996), pages 2-3, 1996.
Using Temporal Logics for Planning and Control [link]Paper   link   bibtex  
From Statistical Knowledge Bases to Degrees of Belief. Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. Artif. Intell., 87(1-2): 75-143. 1996.
From Statistical Knowledge Bases to Degrees of Belief [link]Paper   link   bibtex  
  1995 (4)
Dynamic Variable Ordering in CSPs. Bacchus, F.; and van Run, P. In Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming (CP-1995), pages 258-275, 1995.
Dynamic Variable Ordering in CSPs [pdf]Paper   link   bibtex  
On the Forward Checking Algorithm. Bacchus, F.; and Grove, A. J. In Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming (CP-1995), pages 292-308, 1995.
On the Forward Checking Algorithm [pdf]Paper   link   bibtex  
Reasoning about Noisy Sensors in the Situation Calculus. Bacchus, F.; Halpern, J. Y.; and Levesque, H. J. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI-1995), pages 1933-1940, 1995.
Reasoning about Noisy Sensors in the Situation Calculus [pdf]Paper   link   bibtex  
Graphical models for preference and utility. Bacchus, F.; and Grove, A. J. In Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence (UAI-1995), pages 3-10, 1995.
Graphical models for preference and utility [pdf]Paper   Graphical models for preference and utility [link]Link   link   bibtex  
  1994 (6)
Forming Beliefs about a Changing World. Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. In Proceedings of the 12th AAAI Conference on Artificial Intelligence (AAAI-1994), pages 222-229, 1994.
Forming Beliefs about a Changing World [pdf]Paper   link   bibtex  
Generating New Beliefs from Old. Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. In Proceedings of the 10th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1994), pages 37-45, 1994.
Generating New Beliefs from Old [pdf]Paper   Generating New Beliefs from Old [link]Link   link   bibtex  
Using New Data to Refine a Bayesian Network. Lam, W.; and Bacchus, F. In Proceedings of the 10th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1994), pages 383-390, 1994.
Using New Data to Refine a Bayesian Network [pdf]Paper   Using New Data to Refine a Bayesian Network [link]Link   link   bibtex  
Downward Refinement and the Efficiency of Hierarchical Problem Solving. Bacchus, F.; and Yang, Q. Artif. Intell., 71(1): 43-100. 1994.
Downward Refinement and the Efficiency of Hierarchical Problem Solving [pdf]Paper   link   bibtex  
A Response to "Believing on the Basis of the Evidence". Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. Computational Intelligence, 10: 21-25. 1994.
A Response to "Believing on the Basis of the Evidence" [link]Paper   link   bibtex  
Learning Bayesian Belief Networks: An Approach Based on the MDL Principle. Lam, W.; and Bacchus, F. Computational Intelligence, 10: 269-294. 1994.
Learning Bayesian Belief Networks: An Approach Based on the MDL Principle [link]Paper   link   bibtex  
  1993 (4)
Generating Degrees of Belief from Statistical Information: An Overview. Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. In Proceedings of the 13th Conference n Foundations of Software Technology and Theoretical Computer Science, pages 318-325, 1993.
Generating Degrees of Belief from Statistical Information: An Overview [pdf]Paper   link   bibtex  
Statistical Foundations for Default Reasoning. Bacchus, F.; Grove, A. J.; Halpern, J. Y.; and Koller, D. In Proceedings of the 13th International Joint Conference on Artificial Intelligence (IJCAI-2007), pages 563-569, 1993.
Statistical Foundations for Default Reasoning [pdf]Paper   link   bibtex  
Using First-Order Probability Logic for the Construction of Bayesian Networks. Bacchus, F. In Proceedings of the 9th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1993), pages 219-226, 1993.
Using First-Order Probability Logic for the Construction of Bayesian Networks [pdf]Paper   Using First-Order Probability Logic for the Construction of Bayesian Networks [link]Link   link   bibtex  
Using Causal Information and Local Measures to Learn Bayesian Networks. Lam, W.; and Bacchus, F. In Proceedings of the 9th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1993), pages 243-250, 1993.
Using Causal Information and Local Measures to Learn Bayesian Networks [pdf]Paper   Using Causal Information and Local Measures to Learn Bayesian Networks [link]Link   link   bibtex  
  1992 (3)
The Expected Value of Hierarchical Problem-Solving. Bacchus, F.; and Yang, Q. In Proceedings of the 11th AAAI Conference on Artificial Intelligence (AAAI-1991), pages 369-374, 1992.
The Expected Value of Hierarchical Problem-Solving [pdf]Paper   link   bibtex  
From Statistics to Beliefs. Bacchus, F.; Grove, A. J.; Koller, D.; and Halpern, J. Y. In Proceedings of the 11th AAAI Conference on Artificial Intelligence (AAAI-1991), pages 602-608, 1992.
From Statistics to Beliefs [pdf]Paper   link   bibtex  
Learning Bayesian Belief Networks. Lam, W.; and Bacchus, F. In Proceedings of the Pacific Rim Conference on Atificial Intelligence (PRICAI-92), pages 1237-1243, 1992.
Learning Bayesian Belief Networks [pdf]Paper   link   bibtex  
  1991 (3)
Default Reasoning From Statistics. Bacchus, F. In Proceedings of the 10th AAAI Conference on Artificial Intelligence (AAAI-1991), pages 392-398, 1991.
Default Reasoning From Statistics [pdf]Paper   link   bibtex  
The Downward Refinement Property. Bacchus, F.; and Yang, Q. In Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI-1991), pages 286-293, 1991.
The Downward Refinement Property [pdf]Paper   link   bibtex  
A Non-Reified Temporal Logic. Bacchus, F.; Tenenberg, J. D.; and Koomen, J. A. G. M. Artif. Intell., 52(1): 87-108. 1991.
A Non-Reified Temporal Logic [pdf]Paper   link   bibtex  
  1990 (5)
Probabilistic Belief Logics. Bacchus, F. In Proceedings of the 9th Eureopean Conference on Artificial Intelligence (ECAI-1990), pages 59-64, 1990.
Probabilistic Belief Logics [pdf]Paper   link   bibtex  
Probability and logic: a reply to Cheeseman. Bacchus, F. Computational Intelligence, 6: 180-183. 1990.
Probability and logic: a reply to Cheeseman [link]Paper   link   bibtex  
Lp—a logic for representing and reasoning with statistical knowledge. Bacchus, F. Computational Intelligence, 6: 209-231. 1990.
Lp—a logic for representing and reasoning with statistical knowledge [link]Paper   link   bibtex  
Representing and Reasoning with Probabilistic Knowledge. Bacchus, F. MIT Press, 1990.
Representing and Reasoning with Probabilistic Knowledge [link]Paper   link   bibtex  
Against Conditionalization. Bacchus, F.; Jr., H. E. K.; and Thalos, M. Synthese, 85: 475-506. 1990.
Against Conditionalization [link]Paper   link   bibtex  
  1989 (3)
A Modest but Semantically Well Founded Inheritance Reasoner. Bacchus, F. In Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-1989), pages 1104-1109, 1989.
A Modest but Semantically Well Founded Inheritance Reasoner [pdf]Paper   link   bibtex  
A Non-Reified Temporal Logic. Bacchus, F.; Tenenberg, J. D.; and Koomen, J. A. G. M. In Proceedings of the 1st International Conference on Principles of Knowledge Representation and Reasoning (KR-1989), pages 2-10, 1989.
A Non-Reified Temporal Logic [pdf]Paper   link   bibtex  
Lp: A Logic for Statistical Information. Bacchus, F. In Proceedings of the 5th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1989), pages 3-14, 1989.
Lp: A Logic for Statistical Information [pdf]Paper   Lp: A Logic for Statistical Information [link]Link   link   bibtex  
  1988 (2)
On probability distributions over possible worlds. Bacchus, F. In Proceedings of the 4th Annual Conference on Uncertainty in Artificial Intelligence (UAI-1988), pages 217-226, 1988.
On probability distributions over possible worlds [link]Link   On probability distributions over possible worlds [pdf]Paper   link   bibtex  
Statistically Founded Degrees of Belief. Bacchus, F. In Proceedings Biennial conference on Artificial Intelligence sponsored by the Canadian Society for Computational Studies of Intelligence (CSCSI-1988), pages 56-66, 1988.
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