This is a list of publications stemming from lab research in reverse chronological order. Most of the publications can be downloaded in Postscript and PDF form. For additional publications, please consult the individual pages of the lab members.
Frank, J., Mannor, S., and Precup, D. (2010) Activity and gait recognition with time-delay embeddings. AAAI.
Guez, A. and Pineau, J. (2010) Multi-tasking SLAM. IEEE Conference on Robotics and Automation, 3-7 May 2010.
Kaplow, R., Atrash, A., and Pineau, J. (2010) Variable resolution decomposition for robotic navigation under a POMDP framework. IEEE Conference on Robotics and Automation, 3-7 May 2010.
West, R., Precup, D., and Pineau, J. (2009) Completing Wikipedia's Hyperlink Structure through Dimensionality Reduction. In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM'09), pp. 1097-1106, Hong Kong.
Pineau, J., Guez, A., Vincent, R., Panuccio, G. and Avoli, M. (2009) Treating epilepsy via adaptive neurostimulation: a reinforcement learning approach. International Journal of Neural Systems 19(4) 227-240.
Atrash, A., Kaplow, R., Villemure, J., West, R., Yamani, H., Pineau, J. (2009) Development and Validation of a Robust Speech Interface for Improved Human-Robot Interaction. International Journal of Social Robotics.
Frank, J., Mannor, S., and Precup, D. (2008) Reinforcement learning in the presence of rare events. 25th Annual International Conference on Machine Learning. pp. 336-343.
Warrick, P. A., Hamilton, E. F., Precup, D., and Kearney, R. E. (2008) Detecting the temporal extent of the impulse response function from intra-partum cardiotocography for normal and hypoxic fetuses. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. pp. 2797-2800.
Izadi, M. T., and Precup, D. (2008) Point-based planning for predictive state representations. In Bergler, S., editor, Advances in Artificial Intelligence, 21st Conference of the Canadian Society for Computational Studies of Intelligence, pp. 126-137.
Chatzikokolakis, K., Palamidessi, C., and Panangaden, P. (2008) On the bayes risk in information-hiding protocols. Journal of Computer Security, 2008, v. 16, n. 5, pp. 531-57.
Precup, D., Taylor, J., and Panangaden, P. (2008) Bounding performance loss in approximate MDP homomorphisms. Neural Information Processing Systems.
Ross, S., Chaib-draa, B., and Pineau, J. (2008) Bayes-adaptive POMDPs. Neural Information Processing Systems.
Ross, S., Pineau, J., and Chaib-draa, B. (2008) Theoretical analysis of heuristic search methods for online POMDPs. Neural Information Processing Systems.
Doshi, F., Pineau, J., and Roy, N. (2008) Reinforcement learning with limited reinforcement: Using Bayes risk for active learning in POMDPs. 25th Annual International Conference on Machine Learning.
Chatzikokolakis, K., Palamidessi, C., and Panangaden, P. (2008) Anonymity protocols as noisy channels. Information and Computation, February 2008, v. 206, n. 2-4, pp. 378-401.
Ross, S., Chaib-draa, B., and Pineau, J. (2008) Bayesian reinforcement learning in continuous POMDPs with application to robot navigation. IEEE International Conference on Robotics and Automation (ICRA), 2008.
Fard, M. M., Pineau, J., and Sun, P. (2008) A variance analysis for POMDP policy evaluation. AAAI Conference on Artificial Intelligence, 2008.
Guez, A., Vincent, R. D., Avoli, M. and Pineau, J. (2008) Adaptive treatment of epilepsy via batch-mode reinforcement learning20th Conference on Innovative Applications of Artificial Intelligence.
Ross, S., and Pineau, J. (2008) Model-based bayesian reinforcement learning in large structured domains. Conference on Uncertainty in Artificial Intelligence (UAI), 2008.
Ross, S., Pineau, J., Paquet, S., and Chaib-draa, B.) Online planning algorithms for POMDPs. Journal of Artificial Intelligence Research (JAIR), 2008, v. 32, pp. 663-704.
Delbecque, Y., and Panangaden, P. (2008) Game semantics for quantum stores. 24th Annual Conference on Foundations of Programming Semantics, May 2008.
Martin, K., and Panangaden, P. (2008) A technique for verifying measurements. 24th Annual Conference on Foundations of Programming Semantics, May 2008.
Vincent, R. D., Pineau, J., de Guzman, P. and Avoli, M. (2007) Recurrent boosting for classification of natural and synthetic time-series data. In Proceedings of the 20th Canadian Conference on Artificial Intelligence, 192-203.
Ross, S. and Chaib-draa B. (2007) AEMS: An anytime online search algorithm for approximate policy refinement in large POMDPs. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-07), 2592-2598.
Castro, P. S. and Precup, D. (2007) Using linear programming for Bayesian exploration in Markov Decision Processes. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-07), 2437-2442.
Hundt, C., Panangaden, P., Pineau, J., and Precup, D. (2006) Representing Systems with Hidden State. Proceedings of the Twenty-First National Conference on Artificial Intelligence, Boston, Massachusetts.
Ferns, N., Castro, P., Precup, D., and Panangaden, P. (2006) Methods for Computing State Similarity in Markov Decision Processes. Proceedings on the Conference on Uncertainty in AI (UAI).
Burfoot, D., Pineau, J. and Dudek, G. (2006) RRT-Plan: a randomized algorithm for STRIPs planning. In Proceedings of the International Conference on Automated Planning and Scheduling.
Izadi, M.T., Precup, D., and Azar, D. (2006) Belief selection in point-based planning algorithms for POMDPs In Proceedings of the National Conference on Artificial Intelligence. Quebec City, Canada.
Gupta, V., Jagadeesan, R., and Panangaden, P. (2006) Approximate reasoning for real-time probabilistic processes. Logical Methods in Computer Science 2(1).
Chatzikokolakis, K., Palamidessi, C., and Panangaden, P. (2006) Anonymity Protocols as Noisy Channels. Post-conference proceedings of the Second Symposium on Trustworthy Global Computing, To appear in Lecture Notes In Computer Science, Springer-Verlag.
Bouchard-Cote, A., Ferns, N., Panangaden, P., and Precup, D. (2005) An approximation algorithm for labelled Markov processes: towards realistic approximation. Proceedings of the 2nd International Conference on the Quantitative Evaluation of Systems, Torino, Italy, 54-61.
Ferns, N., Panangaden, P., and Precup, D. (2005) Metrics for Markov Decision Processes with Infinite State Spaces. Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, Edinburgh, U.K., 201-208.
Izadi, M.T. and Precup, D. (2005) Model minimization by linear PSR. In Proceedings of the 19th International Joint Conference in Artificial Intelligence, 1749.
Izadi, M.T., Rajwade, A.V., and Precup, D. (2005) Using core beliefs for point-based value iteration. In Proceedings of the 19th International Joint Conference in Artificial Intelligence, 1751.
Izadi, M.T. and Precup, D. (2005) Using rewards for belief state updates in partially observable Markov decision processes. In Proceedings of the 16th European Conference on Machine Learning, LNCS 3720, 593-600.
Jaulmes, R., Pineau, J., & Precup, D. (2005) Active learning in partially observable Markov decision processes. In Proceedings of the 16th European Conference on Machine Learning, LNCS 3270, 601-608.
Keller, P., Duguay, F.-O., and Precup, D. (2004) Redagent: winner of TAC SCM 2003. ACM SIGecom Exchanges, 4(3), 1-8.
Ratich, B. and Precup, D. (2004) Sparse distributed memories for on-line value-based reinforcement learning. In Proceedings of the 15th European Conference on Machine Learning, LNCS 3201, 347-358.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden, P. (2004) A Metric for Labelled Markov Processes. Theoretical Computer Science, 318(3), 323-354.
Danos, V., Desharnais, J., and Panagaden, P. (2004) Labelled Markov Processes: Stronger and Faster Approximations. Electronic Notes in Theoretical Computer Science, 87, 157-203.
Gupta, V., Jagadeesan, R., and Panangaden, P. (2004) Approximate Reasoning for Real-Time Probabilistic Processes. 1st International Conference on Quantitative Evaluation of Systems, Enschede, the Netherlands, 304-313.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden, P. (2003) Approximating Labelled Markov Processes. Information and Computation, 184(1), 160-200.
Desharnais, J. and Panangaden, P. (2003) Continuous Stochastic Logic Characterizes Bisimulation for Continuous-time Markov Processes. Journal of Logic and Algebraic Progamming, special issue on Probabilistic Techniques for the Design and Analysis of Systems, 56, 99-115.
Izadi, M.T. and Precup, D. (2003) A planning algorithm for predictive state representations. In Proceedings of the 18th International Joint Conference on Artificial Intelligence 18, 1520-1521.
Ratich, B. and Precup, D. (2003) Using MDP characteristics to guide exploration in reinforcement learning. In Proceedings of the 14th European Conference on Machine Learning, LNCS 2837, 313-324.
Danos, V., Desharnais, J., and Panangaden, P. (2003) Conditional Expectation and the Approximation of Labeled Markov Processes. Proceedings of the 14th International Conference on Concurrency Theory, CONCUR03, Marseilles, France. LNCS 2761, 477-491.
Desharnais, J., Edalat, A., and Panagaden, P. (2002) Bisimulation for Labeled Markov Processes. Information and Computation 179(2), 163-193.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden, P. (2002) The Metric Analogue of Weak Bisimulation for Probabilistic Processes. Seventeenth Annual IEEE Symposium on Logic in Computer Science, Copenhagen, Denmark, 413-422.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden, P. (2002) Weak bisimulation is sound and complete for pCTL*. Proceedings of 13th International Conference on Concurrency Theory, CONCUR02, Brno, Czech Republic, LNCS 2421, 355-370.
Letia, I.A., Precup, D., Craciun, F. (2001) Developing collaborative Golog agents by reinforcement learning. In Proceedings of the Thirteenth Conference on Intelligent Tools with Artificial Intelligence (ICTAI 2001). IEEE Computer Press
Precup, D., Sutton, R.S., Dasgupta, S. (2001) Off-policy temporal-difference learning with function approximation. In Proceedings of the Eighteenth Conference on Machine Learning (ICML 2001), 417-424. Morgan Kaufmann.
Panagaden, P. (2001) Measure and Probability for Concurrency Theorists. Theoretical Computer Science, 253, 287-309.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden P. (2000) Approximating Labeled Markov Processes. Proceedings of the Fifteenth Annual IEEE Symposium on Logic in Computer Science, Santa Barbara, California, USA, 95-106.
Panagaden, P. (1999) The Category of Markov Processes. ENTCS, 22.
Gupta, V., Jagadeesan, R., and Panangaden, P. (1999) Stochastic Processes as Concurrent Constraint Programs. Proceedings of POPL 99 San Antonio, USA, 189-202.
Desharnais, J., Gupta, V., Jagadeesan, R., and Panangaden, P. (1999) A Metric for Labelled Markov Processes. Proceedings of 10th International Conference on Concurrency Theory, Eindhoven, The Netherlands, LNCS 1664, eds. Jos C. M. Baeten and S. Mauw, 258-273.
Blute, R., Desharnais, J., and Panangaden, P. (1997) Bisimulation for Labelled Markov Processes Proceedings of the Twelfth IEEE Symposium On Logic In Computer Science, Warsaw, Poland.