Peter van Beek

Cheriton School of Computer Science
University of Waterloo

Publications

 

(PDF) Jianmei Guo, Eric Blais, Krzysztof Czarnecki, and Peter van Beek. A Worst-Case Analysis of Constraint-Based Algorithms for Exact Multi-Objective Combinatorial Optimization. Proceedings of the 30th Canadian Conference on Artificial Intelligence, Edmonton, Alberta, May, 2017.

(PDF) Wei Li, Pascal Poupart, and Peter van Beek. Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference. Journal of Artificial Intelligence Research, 40:729-765, 2011. A preliminary version appeared in the Proceedings of the 23rd AAAI Conference on Artificial Intelligence, Chicago, Ill., 337-343, July, 2008 (PDF).

(PDF) Zijie Li and Peter van Beek. Finding small backdoors in SAT instances. Proceedings of the 24th Canadian Conference on Artificial Intelligence, St John's, Newfoundland and Labrador, 269-280, May, 2011.

(PDF) Huayue Wu and Peter van Beek. On portfolios for backtracking search in the presence of deadlines. Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence, Patras, Greece, 231-238, October, 2007. A longer version appears in the International J. of AI Tools, (PDF), 17:835-855, 2008.

(PDF) Huayue Wu and Peter van Beek. On universal restart strategies for backtracking search. Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming, Providence, RI, 681-695, September, 2007.

(PDF) Wei Li, Peter van Beek, and Pascal Poupart. Performing incremental Bayesian inference by dynamic model counting. Proceedings of the 21st National Conference on Artificial Intelligence, Boston, Mass., 1173-1179, July, 2006.

(PDF) Wei Li and Peter van Beek. Guiding real-world SAT solving with dynamic hypergraph separator decomposition. Proceedings of the Sixteenth IEEE International Conference on Tools with Artificial Intelligence, Boca Raton, Florida, 542-548, November, 2004.

(PDF) Xinguang Chen and Peter van Beek. Conflict-directed backjumping revisited. Journal of Artificial Intelligence Research, 14:53-81, 2001.

(PDF) Grzegorz Kondrak and Peter van Beek. A theoretical evaluation of selected backtracking algorithms. Artificial Intelligence, 89:365-387, 1997. A preliminary version of the paper appears in Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Quebec, 541-547, August, 1995.

 

(PDF) Tyrel Russell and Peter van Beek. Lessons Learned from Modelling the NHL Playoff Qualification Problem. Proceedings of the Eighth International Workshop on Constraint Modellig and Reformulation (ModRef'09), Lisbon, Portugal, September, 2009.

(PDF) Fahiem Bacchus, Xinguang Chen, Peter van Beek, and Toby Walsh. Binary vs. non-binary constraints. Artificial Intelligence, 140:1-37, 2002.

(PDF) Adam Beacham, Xinguang Chen, Jonathan Sillito, and Peter van Beek. Constraint programming lessons learned from crossword puzzles. Proceedings of the 14th Canadian Conference on Artificial Intelligence, Ottawa, Ontario, 78-87, June, 2001.

(PDF) Fahiem Bacchus and Peter van Beek. On the conversion between non-binary and binary constraint satisfaction problems. Proceedings of the 15th National Conference on Artificial Intelligence, Madison, Wisconsin, 311-318, July, 1998.

 

(PDF) Lars Hellsten, Gilles Pesant, and Peter van Beek. A domain consistency algorithm for the stretch constraint. Proceedings of the 10th International Conference on Principles and Practice of Constraint Programming, Toronto, Ontario, 290-304, September, 2004.

(PDF) Claude-Guy Quimper, Alejandro Lopez-Ortiz, Peter van Beek, and Alexander Golynski. Improved algorithms for the global cardinality constraint. Proceedings of the 10th International Conference on Principles and Practice of Constraint Programming, Toronto, Ontario, 542-556, September, 2004.

(PDF) Claude-Guy Quimper, Peter van Beek, Alejandro Lopez-Ortiz, Alexander Golynski, and Sayyed Bashir Sadjad. An efficient bounds consistency algorithm for the global cardinality constraint. Proceedings of the 9th International Conference on Principles and Practice of Constraint Programming, Kinsale, Ireland, 600-614, September, 2003. A longer technical report version is available.

(PDF) Alejandro Lopez-Ortiz, Claude-Guy Quimper, John Tromp, and Peter van Beek. A fast and simple algorithm for bounds consistency of the alldifferent constraint. Proceedings of the 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, 245-250, August, 2003. A longer technical report version is available.

 

(PDF) Peter van Beek and Rina Dechter. Constraint tightness and looseness versus local and global consistency. J. of the ACM, 44:549-566, 1997.

(PDF) Rina Dechter and Peter van Beek. Local and global relational consistency. Theoretical Computer Science, 173:283-308, 1997. A preliminary version of the paper appears in Proceedings of the First International Conference on Principles and Practices of Constraint Programming, Cassis, France, 240-257, September, 1995.

(PDF) Peter van Beek and Rina Dechter. On the minimality and global consistency of row-convex constraint networks. J. ACM, 42:543-561, 1995.

(PDF) Peter van Beek. On the inherent level of local consistency in constraint networks. Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, Washington, 368-373, July, 1994.

(PDF) Peter van Beek and Rina Dechter. Constraint tightness versus global consistency. Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, Bonn, Germany, 572-582, May, 1994.

(PDF) Peter van Beek. On the minimality and decomposability of constraint networks. Proceedings of the 10th National Conference on Artificial Intelligence, San Jose, California, 447-452, July, 1992.

 

(PDF) Mirza Beg and Peter van Beek. A Constraint Programming Approach for Integrated Spatial and Temporal Scheduling for Clustered Architectures. ACM Transactions on Embedded Computing Systems, 13(1):14:1-14:23, 2013.

(PDF) Tyrel Russell and Peter van Beek. Detecting Manipulation in Cup and Round Robin Sports Competitions. Proceedings of the 24th IEEE International Conference on Tools with Artificial Intelligence, Athens, Greece, 285-290, November, 2012.

(PDF) Michael Chase, Abid M. Malik, Tyrel Russell, R. Wayne Oldford, and Peter van Beek. A Computational Study of Heuristic and Exact Techniques for Superblock Instruction Scheduling. Journal of Scheduling, 15(6):743-756, 2012.

(PDF) Tyrel Russell and Peter van Beek. A Hybrid Constraint Programming and Enumeration Approach for Solving NHL Playoff Qualification and Elimination Problems. European Journal of Operational Research, 218(3):819-828, 2011.

(PDF) Tyrel Russell and Peter van Beek. An Empirical Study of Seeding Manipulations and Their Prevention. Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, July, 2011

(PDF) Mirza Beg and Peter van Beek. A Constraint Programming Approach for Instruction Assignment. Proceedings of the 15th Workshop on Interaction between Compilers and Computer Architectures (Interact-15), San Antonio, Texas, February, 2011

(PDF) Omer Beg and Peter van Beek. A Graph Theoretic Approach to Cache-Conscious Placement of Data for Direct Mapped Caches. Proceedings of the ACM SIGPLAN International Symposium on Memory Management (ISMM 2010), Toronto, 113-120, June, 2010.

(PDF) Tyrel Russell and Peter van Beek. Determining the Number of Games Needed to Guarantee an NHL Playoff Spot. Proceedings of the Sixth International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2009), Pittsburgh, 233-247, May, 2009.

(PDF) Abid M. Malik, Michael Chase, Tyrel Russell, and Peter van Beek. An Application of Constraint Programming to Superblock Instruction Scheduling. Proceedings of the 14th International Conference on Principles and Practice of Constraint Programming, Sydney, Australia, 97-111, September, 2008.

(PDF) Tyrel Russell and Peter van Beek. Mathematically Clinching a Playoff Spot in the NHL and the Effect of Scoring Systems. Proceedings of the 21st Canadian Conference on Artificial Intelligence, Windsor, Ontario, 234-245, May, 2008.

(PDF) Abid M. Malik, Tyrel Russell, Michael Chase, and Peter van Beek. Optimal superblock instruction scheduling for multiple-issue processors using constraint programming. Technical Report CS-2006-37, School of Computer Science, University of Waterloo, 2006.

(PDF) Abid M. Malik, Jim McInnes, and Peter van Beek. Optimal basic block instruction scheduling for multiple-issue processors using constraint programming. Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence, Washington, DC, 279-287, November, 2006. A longer version appears in the International J. of AI Tools, (PDF), 17:37-54, 2008.

(PDF) Peter van Beek and Kent Wilken. Fast optimal instruction scheduling for single-issue processors with arbitrary latencies. Proceedings of the Seventh International Conference on Principles and Practice of Constraint Programming, Paphos, Cyprus, 625-639, November, 2001.

(PDF) Michael E. Bergen, Peter van Beek, and Tom Carchrae. Constraint-based vehicle assembly line sequencing. Proceedings of the 14th Canadian Conference on Artificial Intelligence, Ottawa, Ontario, 88-99, June, 2001.

(PDF) Peter van Beek and Xinguang Chen. CPlan: A constraint programming approach to planning. Proceedings of the 16th National Conference on Artificial Intelligence, Orlando, Florida, 585-590, July, 1999.

(PDF) Fulu Li, Ioanis Nikolaidis, Peter van Beek. On the design of efficient video-on-demand broadcast schedules. Proceedings of the Seventh International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, College Park, Maryland, 262-269, October, 1999.

(PDF) Don Banks, Peter van Beek, and Amnon Meisels. A heuristic incremental modeling approach to course timetabling. Proceedings of the Twelfth Canadian Conference on Artificial Intelligence, Vancouver, British Columbia, 16-29, June, 1998.

 

(PDF) Colin Lee and Peter van Beek. An Experimental Analysis of Anytime Algorithms for Bayesian Network Structure Learning. Proceedings of the Third Workshop on Advanced Methodologies for Bayesian Networks, Kyoto, Japan, September, 2017.

(PDF) Colin Lee and Peter van Beek. Metaheuristics for Score-and-Search Bayesian Network Structure Learning. Proceedings of the 30th Canadian Conference on Artificial Intelligence, Edmonton, Alberta, May, 2017.

(PDF) Samaneh Hosseini Semnani, Otman A. Basir, and Peter van Beek. Constrained Clustering for Flocking-based Tracking in Maneuvering Target Environment. Robotics and Autonomous Systems, 83:243-250, 2016.

(PDF) Peter van Beek and Hella-Franziska Hoffmann. Machine Learning of Bayesian Networks Using Constraint Programming. Proceedings of the 21st International Conference on Principles and Practice of Constraint Programming, Cork, Ireland, 428-444, September, 2015.

(PDF) Ray Ruvinskiy and Peter van Beek. An Improved Machine Learning Approach for Selecting a Polyhedral Model Transformation. Proceedings of the 28th Canadian Conference on Artificial Intelligence, Halifax, Nova Scotia, 100-113, June, 2015.

(PDF) Hashim Mir, Peter Xu, Rudi Chen, and Peter van Beek. An autofocus heuristic for digital cameras based on supervised machine learning. J. of Heuristics, 21(5):599-616, 2015.

(PDF) Rudi Chen and Peter van Beek. Improving the accuracy and low-light performance of contrast-based autofocus using supervised machine learning. Pattern Recognition Letters, 56:30-37, 2015.

(PDF) Tyrel Russell, Abid M. Malik, Michael Chase, and Peter van Beek. Learning heuristics for the superblock instruction scheduling problem. IEEE Transactions on Knowledge and Data Engineering, 21(10):1489-1502, 2009.

(PDF) Abid M. Malik, Tyrel Russell, Michael Chase, and Peter van Beek. Learning heuristics for basic block instruction scheduling. J. of Heuristics, 14(6):549-569, 2008. A preliminary version of the paper appears in Proceedings of the 15th CASCON, Toronto, Ontario, October, 2005.

 

(PDF) Peter van Beek and Dennis W. Manchak. The design and experimental analysis of algorithms for temporal reasoning. Journal of Artificial Intelligence Research 4:1-18, 1996.

(PDF) Peter van Beek. Reasoning about qualitative temporal information. Artificial Intelligence 58:297-326, 1992. Preliminary versions of the paper appear in Proceedings of the 8th National Conference on Artificial Intelligence, Boston, Massachusetts, 728-734, July, 1990; and in Recent Advances in Qualitative Physics, Boi Faltings and Peter Struss (eds.), The MIT Press, 211-227, 1992.

(PDF) Peter van Beek. Temporal query processing with indefinite information. Artificial Intelligence in Medicine 3:325-339, 1991.

(PDF) Peter van Beek and Robin Cohen. Exact and approximate reasoning about temporal relations. Computational Intelligence 6:132-144, 1990.

(PDF) Marc Vilain, Henry Kautz, and Peter van Beek. Constraint propagation algorithms for temporal reasoning: A revised report. In Readings in Qualitative Reasoning about Physical Systems, Daniel S. Weld and Johan de Kleer (eds.), Morgan-Kaufman, 373-381, 1989.

(PDF) Peter van Beek. Approximation algorithms for temporal reasoning. Proceedings of the 11th International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1291-1296, August, 1989.

 

(PDF) Peter van Beek. An investigation of probabilistic interpretations of heuristics in plan recognition. Proceedings of the Fifth International Conference on User Modeling, Kailua-Kona, Hawaii, 113-120, January, 1996.

(PDF) Robin Cohen, Ken Schmidt, and Peter van Beek. A framework for soliciting clarification from users during plan recognition. Proceedings of the Fourth International Conference on User Modeling, Hyannis, Massachusetts, 11-17, August, 1994.

Peter van Beek, Robin Cohen, and Ken Schmidt. From plan critiquing to clarification dialogue for cooperative response generation. Computational Intelligence, 9:132-154, 1993.

(PDF) Peter van Beek and Robin Cohen. Resolving plan ambiguity for cooperative response generation. Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, Sydney, Australia, 938-944, August, 1991.

Robin Cohen, Fei Song, Bruce Spencer, and Peter van Beek. Exploiting temporal and novel information from the user in plan recognition. User-Modeling and User-Adapted Interaction, 1:125-148, 1991.

Peter van Beek. A model for generating better explanations. Proceedings of the 25th Conference of the Association for Computational Linguistics, Stanford, California, 215-220, July, 1987.

Peter van Beek and Robin Cohen. Towards user-specific explanations from expert systems. Proceedings of the Sixth Canadian Conference on Artificial Intelligence, Montreal, Quebec, 194-198, May, 1986.

 

(PDF) Ray Ruvinskiy. Using Decision Tree Voting to Select a Polyhedral Model Loop Transformation.
MMath thesis, University of Waterloo, School of Computer Science, 2013.

(PDF) Mirza O. Beg. Combinatorial Problems in Compiler Optimization.
PhD thesis, University of Waterloo, School of Computer Science, 2013.

(PDF) Vladimir Pisanov. Novel Value Ordering Heuristics Using Non-Linear Optimization in Boolean Satisfiability.
MMath thesis, University of Waterloo, School of Computer Science, 2012.

(PDF) Tyrel Russell. A Computational Study of Problems in Sports.
PhD thesis, University of Waterloo, School of Computer Science, 2010.

(PDF) Wei Li. Exploiting Structure in Backtracking Algorithms for Propositional and Probabilistic Reasoning.
PhD thesis, University of Waterloo, School of Computer Science, 2010.

(PDF) Zijie Li. Backdoors in Satisfiability Problems.
MMath thesis, University of Waterloo, School of Computer Science, 2009.

(PDF) Abid Malik. Constraint Programming Techniques for Optimal Instruction Scheduling.
PhD thesis, University of Waterloo, School of Computer Science, 2008.

(PDF) Michael Chase. On the Near-Optimality of List Scheduling Heuristics for Local and Global Instruction Scheduling.
MMath thesis, University of Waterloo, School of Computer Science, 2006.

(PDF) Tyrel Russell. Learning Instruction Scheduling Heuristics from Optimal Data.
MMath thesis, University of Waterloo, School of Computer Science, 2006.

(PDF) Huayue Wu. Randomization and Restart Strategies.
MMath thesis, University of Waterloo, School of Computer Science, 2006.

(PDF) Lars Hellsten. Consistency Propagation for Stretch Constraints.
MMath thesis, University of Waterloo, School of Computer Science, 2004.

(PDF) Jonathan Sillito. Improvements to and estimating the cost of backtracking algorithms for constraint satisfaction problems.
MSc thesis, University of Alberta, Department of Computing Science, 2000.

(PDF) Michael Bergen. Constraint-based assembly line sequencing.
MSc thesis, University of Alberta, Department of Computing Science, 2000.

(PDF) Xinguang Chen. A theoretical comparison of selected CSP solving and modeling techniques.
PhD thesis, University of Alberta, Department of Computing Science, 2000.

Donald Banks. A constraint satisfaction approach to timetabling.
MSc thesis, University of Alberta, Department of Computing Science, 1996.

(PDF) Grzegorz Kondrak. A theoretical evaluation of selected backtracking algorithms.
MSc thesis, University of Alberta, Department of Computing Science, 1994.

Kenneth J. Schmidt. Clarification dialogues for plan recognition in advice-giving systems.
MSc thesis, University of Alberta, Department of Computing Science, 1994.

Alan D. Sharpe. An adaptive approach for acquiring missing knowledge.
MSc thesis, University of Alberta, Department of Computing Science, 1993.

(PDF) Peter van Beek. Exact and approximate reasoning about qualitative temporal relations.
PhD thesis, University of Waterloo, Department of Computer Science, 1990.

 

(PDF) Francesca Rossi, Peter van Beek, and Toby Walsh. Constraint Programming. Chapter 4 in Handbook of Knowledge Representation, Handbook of Knowledge Representation, B. Porter, V. Lifschitz, F. van Harmelen (eds.), Elsevier, 2007.

(PDF) Peter van Beek. Backtracking search algorithms. Chapter 4 in Handbook of Constraint Programming, F. Rossi, P. van Beek, T. Walsh (eds.), Elsevier, 2006.

 

Marina Sokolova and Peter van Beek (eds.), Proceedings of the 27th Canadian Conference on Artificial Intelligence, Montréal, 2014. Appears as: Lecture Notes in Artificial Intelligence 8436, Springer.

Francesca Rossi, Peter van Beek, and Toby Walsh (eds.), Handbook of Constraint Programming, Handbook of Constraint Programming, Elsevier, 2006.

Peter van Beek (ed.). Proceedings of the 11th International Conference on Principles and Practice of Constraint Programming, Sitges, Spain, 2005. Appears as: Lecture Notes in Computer Science 3709, Springer.