Craig Boutilier's Recent Papers

biography research interests research group duties/service teaching citation profiles home

Craig's Google Scholar profile
to make up for lack of organization on this page!

Embedding-Aligned Language Models: Guy Tennenholtz, Yinlam Chow, Chih-wei Hsu, Lior Shani and Anthony Liang, Craig Boutilier.
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-24), Vancouver, to appear (2024).
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval: Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Craig Boutilier and Maryam Karimzadehgan.
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-24), Vancouver, to appear (2024).
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning: Anthony Liang, Guy Tennenholtz, Yinlam Chow, Chih-wei Hsu, Erdem Biyik and Craig Boutilier.
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS-24), Vancouver, to appear (2024).
Factual and Personalized Recommendations using Language Models and Reinforcement Learning: Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-wei Hsu, Aza Tulepbergenov, Mohammad Ghavamzadeh and Craig Boutilier.
First Conference on Language Modeling (COLM-24), 37pp., Philadephia (2024).
Model-Free Preference Elicitation: Carlos Martin Wang, Craig Boutilier, Tuomas Sandholm and Ofer Meshi.
Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), pp.3493-3503, Jeju, South Korea (2024).
Demystifying Embedding Spaces using Large Language Models: Guy Tennenholtz, Yinlam Chow, Chih-wei Hsu, Jihwan Jeong, Lior Shani, Aza Tulepbergenov, Deepak Ramachandran, Martin Mladenov, and Craig Boutilier.
Proceedings of the 12th International Conference on Learning Representations (ICLR-24), Vienna (2024).
Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization: Craig Boutilier, Martin Mladenov and Guy Tennenholtz.
Proceedings of 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp.22575-22583, Vancouver (2024).

See Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models, 2023 (arXiv:2309.06375) for a significantly expanded version of the paper
Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies: Chih-wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz and Craig Boutilier.
Proceedings of the 47th International ACM/SIGIR Conference on Research and Development in Information Retrieval (SIGIR-24, Industry Track), pp.2925-2929, Washington, DC (2024).
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors: Christina Göpfert, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh and Craig Boutilier.
ACM Transactions on Recommender Systems, 2(4), pp.1-37 (2024).
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis: Jonathan Stray, Alon Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloe Bakalar, Lex Beattie, Michael Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra and Nina Vasan.
ACM Transactions on Recommender Systems, 2(3), pp.1-57 (2023).

See arXiv:2207.10192 for early (2022) version of the paper.
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models: Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh Kangwook Lee, and Kimin Lee.
Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS-23), New Orleans (2023).
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management: Dhawal Gupta, Yinlam Chow, Aza Tulepbergenov, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS-23), New Orleans (2023).
Aligning Text-to-Image Models using Human Feedback: Kimin Lee. Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh and Shixiang Shane Gu.
arXiv:2302.12192 (2023).
Model-Free Preference Elicitation: Carlos Martin, Craig Boutilier and Ofer Meshi.
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World (RealML-23), New Orleans (2023).
Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems: Siddharth Prasad, Martin Mladenov and Craig Boutilier.
RecSys 2023 Workshop on Causality, Counterfactuals & Sequential Decision-Making (CONSEQUENCES-23), Singapore (2023).

See workshop extended abstract here or full arXiv version (arXiv:2309.00940).
Reinforcement Learning with History-Dependent Dynamic Contexts: Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, and Craig Boutilier.
Proceedings of the 40th International Conference on Machine Learning (ICML-23), pp.34011-34053, Honolulu (2023).
Preference Elicitation for Music Recommendations: Ofer Meshi, Jon Feldman, Li Yang, Ben Scheetz, Yanli Cai, Mohammadhossein Bateni, Corbyn Salisbury, Vikram Aggarwal and Craig Boutilier.
ICML 2023 Workshop on The Many Facets of Preference-Based Learning (MFPL-23), Honolulu (2023).
A Mixture-of-Expert Approach to RL-based Dialogue Management: Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the Eleventh International Conference on Learning Representations (ICLR-23), Kigali, Rwanda (2023).
Preference Elicitation with Soft Attributes in Interactive Recommendation: Erdem Biyik and Fan Yao, Yinlam Chow, Alex Haig, Chih-wei Hsu, Mohammad Ghavamzadeh and Craig Boutilier.
arXiv:2311.02085 (2023).
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning: Deborah Cohen and Moonkyung Ryu, Yinlam Chow, Orgad Keller and Ido Greenberg and Avinatan Hassidim and Michael Fink and Yossi Matias and Idan Szpektor and Craig Boutilier and Gal Elidan.
arXiv:2208.02294 (2022).
An Adversarial Variational Inference Approach for Travel Demand Calibration of Urban Traffic Simulators: Martin Mladenov, Sanjay Ganapathy Subramaniam, Chih-wei Hsu, Neha Arora, Andrew Tomkins, Craig Boutilier and Carolina Osorio.
Proceedings of the 30th ACM SIGSPATIAL Intl. Conf. on Advances in Geographic Information Systems (SIGSPATIAL-22), pp.6:1-6:4, Seattle (2022).
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors: Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran and Craig Boutilier.
Proceedings of WWW '22: The Web Conference 2022, pp.2411-2421, Lyon, France (2022).
IMO³: Interactive Multi-Objective Off-Policy Optimization: Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton and Craig Boutilier.
Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI-22), pp.3523-3529, Vienna (2022).
Thompson Sampling with a Mixture Prior: Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AIStats-22), PMLR 151:7565-7586 (2022).
Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities: Filip Radlinksi, Craig Boutilier, Deepak Ramachandran and Ivan Vendrov.
Proceedings of 36th AAAI Conference on Artificial Intelligence (AAAI-22), pp.12287-12293, 2022.
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report: Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, and Toby Walsh.
Stanford University, Stanford, CA, September 2021.
The extensive 82-page report of the Second AI100 Study Panel: AI100 (The One Hundred Year Study on Artificial Intelligence) is a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society. It provides a report on the state of artificial intelligence and its influences on society every five years.
Meta-Thompson Sampling: Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier and Csaba Szepesvari.
Proceedings of the Thirty-eighth Conference on Machine Learning (ICML-21), pp.5884-5893 (2021).

See arXiv:2102.06129 for an expanded version of the paper
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems: Martin Mladenov, Chih-wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov and Craig Boutilier.
arXiv preprint: arXiv:2103.08057 (2021).

(a) See also a short demonstration paper: Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG , appeared at 14th ACM Conference on Recommender Systems (RecSys-20), pp.591-593 (2020)

(b) See also the GitHub RecSim NG Repo for scalable, distributed, modular framework for specifying, learning from data, and executing complex recommender ecosystem environments suitable for developing and benchmarking various algorithms (RL, exploration/bandits, multiagent, fairness, etc.).
Towards Content Provider-Aware Recommendation Systems: A Simulation Study on Interplays among User and Provider Utilities: Ruohan Zhan, Konstantina Christakopoulou, Elaine Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi and Minmin Chen.
Proceedings of WWW '21: The Web Conference 2021, pp.3872-3883, Ljubljana, Slovenia (2021).
Latent Bandits Revisited: Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed and Craig Boutilier.
Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-20), pp.13423--13433, Vancouver (2020).

See arXiv:2006.08714 for an expanded version of the paper
Differentiable Meta-Learning of Bandit Policies: Craig Boutilier, Chih-wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvari and Manzil Zaheer.
Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-20), pp.2122--2134, Vancouver (2020).

See arXiv:2002.06772 for an expanded version of the paper
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach (pre-conference version): Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel and Craig Boutilier.
Proceedings of the Thirty-seventh International Conference on Machine Learning (ICML-20), pp.6987-6998, Vienna, Austria.
ConQUR: Mitigating Delusional Bias in Deep Q-Learning: DiJia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans and Craig Boutilier.
Proceedings of the Thirty-seventh International Conference on Machine Learning (ICML-20), pp.9187-9195, Vienna, Austria.
BRPO: Batch Residual Policy Optimization: Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi and Craig Boutilier.
Proceedings of the Twenty-ninth International Joint Conference on Artificial Intelligence (IJCAI-20), pp.2824-2830, Yokohama, Japan

See arXiv:2002.05522 for an expanded version of the paper
On the Equivalence of Optimal Recommendation Sets and Myopically Optimal Query Sets: Paolo Viappiani and Craig Boutilier.
Artificial Intelligence, Article 103328, 62pp. (2020).
Some of the material in this article appeared at NIPS10 and RecSys09 (see below).
Preference Elicitation and Robust Winner Determination for Single- and Multi-winner Social Choice: Tyler Lu and Craig Boutilier.
Artificial Intelligence 279, Article 103203, 32pp. (2020).
Some of the material in this article appeared at IJCAI-11 and IJCAI-13 (see below).
CAQL: Continuous Action Q-Learning: Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja and Craig Boutilier.
Proceedings of the Eighth International Conference on Learning Representations (ICLR-20), to appear, Addis Ababa, Ethiopia (2020).

See arXiv:1909.12397 for an earlier version of the paper.
Gradient-based Optimization for Bayesian Preference Elicitation: Ivan Vendrov, Qingqing Huang, Tyler Lu and Craig Boutilier.
Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp.10292-10301, New York (2020).
Randomized Exploration in Generalized Linear Bandits: Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AIStats-20), pp.2066-2076, Palermo, Italy (2020).

See arXiv:1906.08947 for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
RecSim: A Configurable Simulation Platform for Recommender Systems: Eugene Ie, Chih-wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu and Craig Boutilier.
arXiv preprint: arXiv:1909.04847 (2019).

See also the GitHub RecSim Repo for specifying and executing recommender systems environments suitable for developing and benchmarking RL, bandit, and other interactive approaches for recommendation.
SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets: Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Tushar Chandra and Craig Boutilier.
Proceedings of the Twenty-eighth International Joint Conference on Artificial Intelligence (IJCAI-19), pp.2592-2599, Macau, China (2019).

See arXiv:1905.12767 for a related and expanded paper (with additional material and authors).
Advantage Amplification in Slowly Evolving Latent-State Environments: Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans and Craig Boutilier.
Proceedings of the Twenty-eighth International Joint Conference on Artificial Intelligence (IJCAI-19), pp.3165-3172, Macau, China (2019).

See arXiv:1905.13559 for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
Perturbed-History Exploration in Stochastic Multi-Armed Bandits: Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the Twenty-eighth International Joint Conference on Artificial Intelligence (IJCAI-19), pp.2786-2793, Macau, China (2019).

See arXiv:1902.10089 for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
Empathetic Decision Making in Social Networks: Amirali Salehi-Abari, Craig Boutilier and Kate Larson
Artificial Intelligence 275, pp.174--203 (2019).
An earlier, shorter version of this article appeared at AAMAS-14 (see below).
Perturbed-History Exploration in Stochastic Linear Bandits: Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh and Craig Boutilier.
Proceedings of the Thirty-fifth Conference on Uncertainty in Artificial Intelligence (UAI-19), pp.176-186, Tel Aviv (2019).
Experiential Preference Elicitation for Autonomous Heating and Cooling Systems: Andrew Perrault, and Craig Boutilier.
Proceedings of the Eighteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), pp.431-439, Montreal (2019).
Seq2Slate: Re-ranking and Slate Optimization with RNNs: Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Chi, Elad Eban, Xiyang Luo, Alan Mackey and Ofer Meshi.
arXiv preprint: arXiv:1810.02019 (2019).
Non-delusional Q-learning and Value Iteration: Tyler Lu, Dale Schuurmans and Craig Boutilier.
Proceedings of the Thirty-second Conference on Neural Information Processing Systems (NeurIPS-18), pp.9971-9981, Montreal (2018).
Winner, Best Paper Award.
This version includes an appendix with additional discussion, proofs and experiments that did not fit in the camera-ready paper.
Data Center Cooling using Model-predictive Control: Nevena Lazic, Craig Boutilier, Tyler Lu, Eehern Wong, Binz Roy, MK Ryu and Greg Imwalle.
Proceedings of the Thirty-second Conference on Neural Information Processing Systems (NIPS-18), pp.3818-3827, Montreal (2018).
Planning and Learning with Stochastic Action Sets: Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov and Dale Schuurmans.
Proceedings of the Twenty-seventh International Joint Conference on Artificial Intelligence (IJCAI-18), pp.4674-4682, Stockholm (2018).

See arXiv:1805.02363 for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
Logistic Markov Decision Processes: Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan and Tyler Lu.
Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), pp.2486-2493, Melbourne (2017).

See here for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
Multiple-Profile Prediction-of-Use Games: Andrew Perrault, and Craig Boutilier.
Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), pp.366-373, Melbourne (2017).
An extended version of this paper appears as Chapter 17 of Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers, São Paulo, Brazil, Revised Selected Papers, pp.275-295, Springer Lecture Notes in AI, 2017.
Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes: Craig Boutilier and Tyler Lu.
Proceedings of the Thirty-second Conference on Uncertainty in Artificial Intelligence (UAI-16), pp.52-61, New York (2016).

See here for an expanded version of the paper (including proofs that did not fit in the camera-ready paper).
Incomplete Information and Communication in Voting (password for download from CUP: cam1CSC): Craig Boutilier and Jeff Rosenshein.
Chapter 10 of Handbook of Computational Social Choice, F. Brandt, V. Conitzer, U. Endriss, J. Lang, A. D. Procaccia (eds), pp.223-260, Cambridge University Press (2016).
You can download the book (chapter) from Cambridge Univ. Press with the password cam1CSC (password provided permission of CUP).
More information on the Handbook of Computational Social Choice
Optimal Social Choice Functions: A Utilitarian View: Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia and Or Sheffet.
Artificial Intelligence 227:190-213 (2015).
Winner, 2022 AIJ Prominent Paper Award
An earlier, shorter version of this article appeared at ACM EC-12 (see below).
Preference-oriented Social Networks: Group Recommendation and Inference: Amirali Salehi-Abari and Craig Boutilier.
Proceedings of the 9th ACM Conference on Recommender Systems (RecSys-15), pp.35-42, Vienna (2015).
Optimal Group Manipulation in Facility Location Problems: Xin Sui and Craig Boutilier.
Proceedings of the Fourth Conference on Algorithmic Decision Theory (ADT-15), pp.505-520, Lexington, KY (2015).
Approximately Stable Pricing for Coordinated Purchasing of Electricity: Andrew Perrault, and Craig Boutilier.
Proceedings of the Twenty-fourth International Joint Conference on Artificial Intelligence (IJCAI-15), pp.2624-2631, Buenos Aires (2015).
Approximately Strategy-proof Mechanisms for (Constrained) Facility Location: Xin Sui, and Craig Boutilier.
Proceedings of the Fourteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), pp.605-613, Instanbul (2015).
Value-directed Compression of Large-scale Assignment Problems: Tyler Lu, and Craig Boutilier.
Proceedings of the Twenty-ninth AAAI Conference on Artificial Intelligence (AAAI-15), pp.1182-1190, Austin, TX (2015).
The Pricing War Continues: On Competitive Multi-Item Pricing: Omer Lev, Joel Oren, Craig Boutilier. and Jeffrey S. Rosenshein,
Proceedings of the Twenty-ninth AAAI Conference on Artificial Intelligence (AAAI-15), pp.972-978, Austin, TX (2015).
Effective Sampling and Learning for Mallows Models with Pairwise-Preference Data: Tyler Lu, and Craig Boutilier.
Journal of Machine Learning Research, 15(1):3783-3829 (2014).
On the Value of using Group Discounts under Price Competition: Reshef Meir, Tyler Lu, Moshe Tennenholtz and Craig Boutilier.
Artificial Intelligence 216, pp.163-178 (2014).
An earlier, shorter version of this article appeared at AAAI-13 (see below).
Robust Winners and Winner Determination Policies under Candidate Uncertainty: Craig Boutilier, Jérôme Lang Joel Oren and Héctor Palacios.
Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence (AAAI-14), pp.1391-1397, Quebec City (2014).
An earlier version with the same title appeared at COMSOC-12 (see below).
Preference Elicitation and Interview Minimization in Stable Matchings: Joanna Drummond and Craig Boutilier.
Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence (AAAI-14), pp.645-653, Quebec City (2014).
A Game-theoretic Analysis of Catalog Optimization: Joel Oren, Nina Narodytska, and Craig Boutilier.
Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence (AAAI-14), pp.1463-1470, Quebec City (2014).
Regret-based Optimization and Preference Elicitation for Stackelberg Security Games with Uncertainty.: Thanh H. Nguyen, Amulya Yadav, Bo An, Milind Tambe, and Craig Boutilier.
Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence (AAAI-14), pp.756-762, Quebec City (2014).
Empathetic Social Choice on Social Networks: Amirali Salehi-Abari, and Craig Boutilier.
Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-14), pp.693-700, Paris (2014).
An earlier version with the same title appeared at COMSOC-12 (see below).
Efficient Coordinated Power Distribution on Private Infrastructure: Andrew Perrault, and Craig Boutilier.
Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-14), pp.805-812, Paris (2014).
Elicitation and Approximately Stable Matching with Partial Preferences: Joanna Drummond and Craig Boutilier.
Proceedings of the Twenty-third International Joint Conference on Artificial Intelligence (IJCAI-13), pp.97-105, Beijing (2013).
Multi-dimensional Single-peaked Consistency and its Approximations: Xin Sui, Alex Nienaber, and Craig Boutilier.
Proceedings of the Twenty-third International Joint Conference on Artificial Intelligence (IJCAI-13), pp.375-382, Beijing (2013).
Analysis and Optimization of Multi-dimensional Percentile Mechanisms: Xin Sui, Craig Boutilier and Tuomas Sandholm.
Proceedings of the Twenty-third International Joint Conference on Artificial Intelligence (IJCAI-13), pp.367-374, Beijing (2013).
Efficient Vote Elicitation under Candidate Uncertainty: Joel Oren, Yuval Filmus, and Craig Boutilier.
Proceedings of the Twenty-third International Joint Conference on Artificial Intelligence (IJCAI-13), pp.309-316, Beijing (2013).
Multi-winner Social Choice with Incomplete Preferences: Tyler Lu and Craig Boutilier.
Proceedings of the Twenty-third International Joint Conference on Artificial Intelligence (IJCAI-13), pp.263-270, Beijing (2013).
On the Value of using Group Discounts under Price Competition: Reshef Meir, Tyler Lu, Moshe Tennenholtz and Craig Boutilier.
Proceedings of the Twenty-seventh Conference on Artificial Intelligence (AAAI-13), pp.683-689, Bellevue, WA (2013).
Honorable Mention, Outstanding Paper Award.

See here for an expanded version of the paper (with proofs that did not fit in the camera-ready paper).
People, Sensors, Decisions: Customizable and Adaptive Technologies for Assistance in Healthcare.: Jesse Hoey, Craig Boutilier, Pascal Poupart, Patrick Olivier, Andrew Monk, Alex Mihailadis.
ACM Transactions on Intelligent Interactive Systems, 2(4):Article 20, 36pp. (2012)
Robust Winners and Winner Determination Policies under Candidate Uncertainty: Craig Boutilier, Jérôme Lang Joel Oren and Héctor Palacios.
The Fourth International Workshop on Computational Social Choice (COMSOC-2012), Kraków, Poland, to appear (2012).
Empathetic Social Choice on Social Networks: Amirali Salehi-Abari, and Craig Boutilier.
The Fourth International Workshop on Computational Social Choice (COMSOC-2012), Kraków, Poland, to appear (2012).
Analysis and Optimization of Multi-dimensional Percentile Mechanisms: Xin Sui, Craig Boutilier and Tuomas Sandholm.
The Fourth International Workshop on Computational Social Choice (COMSOC-2012), Kraków, Poland, to appear (2012).
Computational Decision Support: Regret-based Models for Optimization and Preference Elicitation: Craig Boutilier.
In Comparative Decision Making: Analysis and Support Across Disciplines and Applications, P. H. Crowley and T. R. Zentall, eds., Oxford University Press, pp.423-453 (2013).
An overview of regret-based optimization and preference elicitation for a broad, multi-disciplinary audience.
Bayesian Vote Manipulation: Optimal Strategies and Impact on Welfare: Tyler Lu, Pingzhong Tang, Ariel D. Procaccia and Craig Boutilier.
Proceedings of the Twenty-eighth Conference on Uncertainty in Artificial Intelligence (UAI-12), pp.543-553, Catalina, CA (2012).

See here for an expanded version of the paper (with proofs that did not fit in the camera-ready paper).
Matching Models for Preference-sensitive Group Purchasing: Tyler Lu and Craig Boutilier.
Proceedings of the Thirteenth ACM Conference on Electronic Commerce (EC'12), pp.723-740, Valencia, Spain (2012).

See here for an expanded version of the paper (with proofs and data set details that did not fit in the camera-ready paper).
Optimal Social Choice Functions: A Utilitarian View: Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia and Or Sheffet.
Proceedings of the Thirteenth ACM Conference on Electronic Commerce (EC'12), pp.197-214, Valencia, Spain (2012).

See here for an expanded version of the paper (with proofs that did not fit in the camera-ready paper).
Eliciting Forecasts from Self-interested Experts: Scoring Rules for Decision Makers: Craig Boutilier.
Proceedings of the Eleventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS-12), pp.737-784, Valencia, Spain (2012).
An earlier, longer working paper with proofs of main results is also available as arXiv:1106.2489, 2011.
A Dynamic Rationalization of Distance Rationalizability: Craig Boutilier and Ariel D. Procaccia.
Proceedings of the Twenty-sixth Conference on Artificial Intelligence (AAAI-12), pp.1278-1284, Toronto (2012).
Active Learning for Matching Problems: Laurent Charlin Rich Zemel and Craig Boutilier.
Proceedings of the Twenty-ninth International Conference on Machine Learning (ICML 2012), Edinburgh, 8pp. (2012).
Sequentially Optimal Repeated Coalition Formation under Uncertainty: Georgios Chalkiadakis and Craig Boutilier.
Autonomous Agents and Multiagent Systems, 24(3):441-484 (2012).
Link to Official Paper at journal website (Springer).
POMDP Models for Assistive Technology: Jesse Hoey, Pascal Poupart, Craig Boutilier, Alex Mihailadis,
In Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions. E. Sucar, E. Morales and J. Hoey (eds.), IGI Global, pp. 33-62 (2011).
An earlier, shorter paper with the same title also appeared in the Proceedings of the AAAI Fall Symposium on Caring Machines: AI in Eldercare, pp.51-58, Arlington, VA (2005).
Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs: Tyler Lu and Craig Boutilier.
Proceedings of the Second Conference on Algorithmic Decision Theory (ADT-11), Piscataway, NJ, pp.134-149 (2011).
Learning Complex Concepts using Crowdsourcing: A Bayesian Approach: Paolo Viappiani, Sandra Zilles, Howard Hamilton, and Craig Boutilier.
Proceedings of the Second Conference on Algorithmic Decision Theory (ADT-11), Piscataway, NJ, pp.277-291 (2011).
Probabilistic and Utility-theoretic Models in Social Choice: Challenges for Learning, Elicitation, and Manipulation . (A short position paper.): Craig Boutilier and Tyler Lu.
IJCAI-11 Workshop on Social Choice and Artificial Intelligence , pp.7-9, Barcelona (2011).
Learning Mallows Models with Pairwise Preferences: Tyler Lu and Craig Boutilier.
Proceedings of the Twenty-Eighth International Conference on Machine Learning (ICML 2011), pp.145-152, Bellevue, WA (2011).
Robust Approximation and Incremental Elicitation in Voting Protocols: Tyler Lu and Craig Boutilier.
Proceedings of the Twenty-second International Joint Conference on Artificial Intelligence (IJCAI-11), pp.287-293, Barcelona (2011).
Robust Online Optimization of Reward-uncertain MDPs: Kevin Regan and Craig Boutilier.
Proceedings of the Twenty-second International Joint Conference on Artificial Intelligence (IJCAI-11), pp.2165-2171, Barcelona (2011).
Budgeted Social Choice: From Consensus to Personalized Decision Making: Tyler Lu and Craig Boutilier.
Proceedings of the Twenty-second International Joint Conference on Artificial Intelligence (IJCAI-11), pp.280-286, Barcelona (2011).
An earlier version (longer and with proofs of main results) appeared at COMSOC-10 (see below).
Eliciting Additive Reward Functions for Markov Decision Processes: Kevin Regan and Craig Boutilier.
Proceedings of the Twenty-second International Joint Conference on Artificial Intelligence (IJCAI-11), pp.2159-2164, Barcelona (2011).
Efficiency and Privacy Tradeoffs in Mechanism Design: Xin Sui and Craig Boutilier.
Proceedings of the Twenty-fifth National Conference on Artificial Intelligence (AAAI-11), pp.738-744, San Francisco (2011).
A Framework for Optimizing Paper Matching: Laurent Charlin Rich Zemel and Craig Boutilier.
Proceedings of the Twenty-seventh Conference on Uncertainty in Artificial Intelligence (UAI-11), pp.86-95, Barcelona (2011).
Recommendation Sets and Choice Queries: There Is No Exploration/Exploitation Tradeoff!: Paolo Viappiani and Craig Boutilier.
Proceedings of the Twenty-fifth National Conference on Artificial Intelligence (AAAI-11), NECTAR Track, pp.1571-1574, San Francisco (2011).
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets: Paolo Viappiani and Craig Boutilier.
Advances in Neural Information Processing Systems 23 (NIPS-10), pp.2352--2360, Vancouver (2010).
Budgeted Social Choice: A Framework for Multiple Recommendations in Consensus Decision Making: Tyler Lu and Craig Boutilier.
The Third International Workshop on Computational Social Choice (COMSOC-2010), Düsseldorf, Germany, pp.55-66 (2010).
The Unavailable Candidate Model: A Decision-Theoretic View of Social Choice: Tyler Lu and Craig Boutilier.
Proceedings of the Eleventh ACM Conference on Electronic Commerce (EC'10), pp.263--274, Boston (2010).

See here for an expanded version of the paper including proofs. Note: An earlier, extended abstract "A Decision-Theoretic Model of Rank Aggregation" appeared at the NIPS 2009 Advances in Ranking Workshop, Whistler, BC (2009).
Assessing Regret-based Preference Elicitation with the UTPREF Recommendation System: Darius Braziunas and Craig Boutilier.
Proceedings of the Eleventh ACM Conference on Electronic Commerce (EC'10), pp.219--228, Boston (2010).
Automated Channel Abstraction for Advertising Auctions: William E. Walsh, Craig Boutilier, Tuomas Sandholm, Rob Shields, George Nemhauser, and David C. Parkes ,
Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence (AAAI-10) , pp.887--894, Atlanta GA (2010).
An earlier, extended version appeared at the 5th Advertising Auction Workshop Stanford, CA (2009).
Robust Policy Computation in Reward-uncertain MDPs using Nondominated Policies: Kevin Regan and Craig Boutilier.
Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence (AAAI-10) , pp.1127--1133, Atlanta GA (2010).
Simultaneous Elicitation of Preference Features and Utility: Craig Boutilier, Kevin Regan and Paolo Viappiani.
Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence (AAAI-10) , pp.1160--1167, Atlanta GA (2010).
A preliminary, short version of this paper appeared at the 3rd ACM Conference on Recommender Systems (RecSys-09), New York (2009).
Automated Handwashing Assistance for Persons with Dementia Using Video and a Partially Observable Markov Decision Process: Jesse Hoey, Pascal Poupart, Tammy Craig, Axel von Bertoldi, Craig Boutilier and Alex Mihailadis,
Computer Vision and Image Understanding, 114(5), pp.503--519 (2010).
Automated Channel Abstraction for Advertising Auctions: William E. Walsh, Craig Boutilier, Tuomas Sandholm, Rob Shields, George Nemhauser, and David C. Parkes ,
Proceedings of the 5th Advertising Auction Workshop, , Stanford, CA (2009).
Regret-based Optimal Recommendation Sets in Conversational Recommender Systems: Paolo Viappiani and Craig Boutilier.
Proceedings of the 3rd ACM Conference on Recommender Systems (RecSys-09), pp.101--108, New York (2009).
Preference Elicitation with Subjective Features: Craig Boutilier, Kevin Regan and Paolo Viappiani and Craig Boutilier.
Proceedings of the 3rd ACM Conference on Recommender Systems (RecSys-09), short paper, pp.341--344, New York (2009).
Online Feature Elicitation in Interactive Optimization: Craig Boutilier, Kevin Regan and Paolo Viappiani
Proceedings of the Twenty-Sixth International Conference on Machine Learning (ICML 2009), pp.73--81, Montreal (2009).
Regret-based Reward Elicitation for Markov Decision Processes: Kevin Regan and Craig Boutilier.
Proceedings of the Twenty-fifth Conference on Uncertainty in Artificial Intelligence (UAI-09), pp.444--451, Montreal (2009).
A Probabilistic Mental Model for Estimating Disruption: Bowen Hui, Grant Partridge and Craig Boutilier.
Proceedings of the 2009 Conference on Intelligent User Interfaces (IUI-09), pp.287-296, Sanibel Island, FL (2009).
Practical Solution Techniques for First-order MDPs: Scott Sanner and Craig Boutilier.
Artificial Intelligence 173(5--6), pp.748--788 (2009).
Winner, 2014 AIJ Prominent Paper Award
Elicitation of Factored Utilities: Darius Braziunas and Craig Boutilier.
AI Magazine 29(4):79--92, Winter (2008).
Toward Experiential Utility Elicitation for Interface Customization: Bowen Hui and Craig Boutilier.
Proceedings of the Twenty-fourth Conference on Uncertainty in Artificial Intelligence (UAI-08), pp.298-305, Helsinki (2008).
Expressive Banner Ad Auctions and Model-Based Online Optimization for Clearing: Craig Boutilier, Tuomas Sandholm, David C. Parkes , and William E. Walsh.
Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence (AAAI-08) , pp.30-37, Chicago (2008).
Computing Reserve Prices and Identifying the Value Distribution in Real-world Auctions with Market Disruptions: William E. Walsh. David C. Parkes , Tuomas Sandholm, and Craig Boutilier.
Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence (AAAI-08) , short paper, pp.1499-1502, Chicago (2008).
Sequential Decision Making in Repeated Coalition Formation under Uncertainty: Georgios Chalkiadakis and Craig Boutilier.
Proceedings of the Seventh International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-08), pp.347-354, Estoril, Portugal (2008).
The Need for an Interaction Cost Model in Adaptive Interfaces: Bowen Hui, Sean Gustafson, Pourang Irani, and Craig Boutilier.
Proceedings of the International Conference on Advanced Visual Interfaces (AVI-08), , short paper, pp.458-461, Napoli (2008).
Approximate Solution Techniques for Factored First-order MDPs: Scott Sanner and Craig Boutilier.
Proceedings of the Seventeenth Conference on Automated Planning and Scheduling (ICAPS-07), pp.288-295, Providence, RI (2007).
Minimax Regret-based Elicitation of Generalized Additive Utilities: Darius Braziunas and Craig Boutilier.
Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence (UAI-07), pp.25-32, Vancouver (2007).
You can view the abstract or you can retrieve the paper.
Partial Revelation Automated Mechanism Design: Nathanael Hyafil and Craig Boutilier.
Proceedings of the Twenty-second National Conference on Artificial Intelligence (AAAI-07) , pp.72-78, Vancouver (2007).
You can view the abstract or you can retrieve the paper.
Computing Optimal Subsets: Maxim Binshtok, Ronen I. Brafman, Solomon E. Shimony, Ajay Martin and Craig Boutilier.
Proceedings of the Twenty-second National Conference on Artificial Intelligence (AAAI-07) , pp.1231-1236, Vancouver (2007).
You can view the abstract or you can retrieve the paper.
Coalition Formation under Uncertainty: Bargaining Equilibria and the Bayesian Core Stability Concept: Georgios Chalkiadakis, Evangelos Markakis and Craig Boutilier.
Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-07), pp.400-407, Honolulu (2007).
You can view the abstract or you can retrieve the paper.
Mechanism Design with Partial Revelation: Nathanael Hyafil and Craig Boutilier.
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07) , pp.1333-1340, Hyderabad, India (2007).
You can view the abstract or you can retrieve the paper.
Automated Design of Multistage Mechanisms: Tuomas Sandholm, Vincent Conitzer and Craig Boutilier.
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07) , pp.1500-1506, Hyderabad, India (2007).
You can view the abstract or you can retrieve the paper.
An earlier version appeared at the First International Workshop on Incentive Based Computing, at the IEEE/WIC/ACM International Conference on Web Intelligence (IBC-05), pp.2--12, Compiegne, France (2005).
You can view the abstract or you can retrieve the paper.
Coalitional Bargaining with Agent Type Uncertainty: Georgios Chalkiadakis and Craig Boutilier.
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07) , pp.1227-1232, Hyderabad, India (2007).
You can view the abstract or you can retrieve the paper.
Regret-based Incremental Partial Revelation Mechanisms: Nathanael Hyafil and Craig Boutilier.
Proceedings of the Twenty-first National Conference on Artificial Intelligence (AAAI-06) , pp.672--678, Boston (2006).
You can view the abstract or you can retrieve the paper.
Practical Linear Value-approximation Techniques for First-order MDPs: Scott Sanner and Craig Boutilier.
Proceedings of the Twenty-second Conference on Uncertainty in Artificial Intelligence (UAI-06), Boston (2006).
You can view the abstract or you can retrieve the paper.
Who's Asking For Help? A Bayesian Approach to Intelligent Assistance: Bowen Hui and Craig Boutilier.
International Conference on Intelligent User Interfaces (IUI-06) , pp.186--193, Sydney (2006).
You can view the abstract or you can retrieve the paper.
Preference Elicitation and Generalized Additive Utility: Darius Braziunas and Craig Boutilier.
Proceedings of the Twenty-first National Conference on Artificial Intelligence, (AAAI-06), NECTAR Track, pp.1573--1576, Boston (2006).
Constraint-based Optimization and Utility Elicitation using the Minimax Decision Criterion: Craig Boutilier, Relu Patrascu, Pascal Poupart, and Dale Schuurmans.
Artificial Intelligence 170(8--9), pp.686--713 (2006).
You can view the abstract or you can retrieve the paper.
A Planning System Based on Markov Decision Processes to Guide People with Dementia Through Activities of Daily Living: Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff Fernie, and Alex Mihailadis,
IEEE Transactions on Information Technology in Biomedicine 10(2), pp.323--333 (2006).
You can view the abstract or you can retrieve the paper.
The Influence of "Influence Diagrams": Craig Boutilier.
Decision Analysis 2(4):229-231 (2005).
This is a short commentary on the impact of Howard and Matheson's seminal 1984 paper "Influence Diagrams".
Local Utility Elicitation in GAI Models: Darius Braziunas and Craig Boutilier.
Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence (UAI-05), pp.42--49, Edinburgh (2005).
Winner, Best Paper Award.
You can view the abstract or you can retrieve the paper.
Approximate Linear Programming for First-order MDPs: Scott Sanner and Craig Boutilier.
Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence (UAI-05), pp.509--517, Edinburgh (2005).
You can view the abstract or you can retrieve the paper.
Decision-Theoretic Approach to Task Assistance for Persons with Dementia: Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff Fernie, and Alex Mihailadis,
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05), pp.1293--1299, Edinburgh (2005).
You can view the abstract or you can retrieve the paper.
Regret-based Utility Elicitation in Constraint-based Decision Problems: Craig Boutilier, Relu Patrascu, Pascal Poupart, and Dale Schuurmans.
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05), pp.929--934, Edinburgh (2005).
You can view the abstract or you can retrieve the paper.
New Approaches to Optimization and Utility Elicitation in Autonomic Computing: Relu Patrascu, Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro and William E. Walsh.
Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pp.140--145, Pittsburgh (2005).
You can view the abstract or you can retrieve the paper.
POMDP Models for Assistive Technology: Jesse Hoey, Pascal Poupart, Craig Boutilier, Alex Mihailadis,
Proceedings of the AAAI Fall Symposium on Caring Machines: AI in Eldercare, pp.51-58, Arlington, VA (2005).
Preference Elicitation in Combinatorial Auctions.: Tuomas Sandholm and Craig Boutilier.
Chapter 10 of Combinatorial Auctions, Cramton, Shoham, and Steinberg, eds., MIT Press (2006).
You can retrieve the paper.
A Study of Limited-Precision, Incremental Elicitation in Auctions: Alex Kress and Craig Boutilier.
Working Paper, 2004.
You can view the abstract or you can retrieve the paper.
VDCBPI: an Approximate Scalable Algorithm for Large Scale POMDPs: Pascal Poupart and Craig Boutilier.
Advances in Neural Information Processing Systems 17 ( NIPS-04), pp.1081--1088, Vancouver (2004).
You can view the abstract or you can retrieve the paper.
Regret Minimizing Equilibria and Mechanisms for Games with Strict Type Uncertainty: Nathanael Hyafil and Craig Boutilier.
Proceedings of the Twentieth Annual Conference on Uncertainty in Artificial Intelligence (UAI-04), pp.268--277, Banff, AB (2004).
You can view the abstract or you can retrieve the paper.
Eliciting Bid Taker Non-price Preferences in (Combinatorial) Auctions: Craig Boutilier, Tuomas Sandholm, and Rob Shields.
Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-2004), pp.204--211, San Jose (2004).
You can view the abstract or you can retrieve the paper.
Stochastic Local Search for POMDP Controllers: Darius Braziunas and Craig Boutilier.
Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-2004), pp.690--696, San Jose (2004).
You can view the abstract or you can retrieve the paper.
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty: Georgios Chalkiadakis and Craig Boutilier.
Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-04), New York, NY, pp.1090--1097 (2004).
Honorable Mention, Best Student Paper.
You can view the abstract or you can retrieve the paper.
Bounded Finite State Controllers: Pascal Poupart and Craig Boutilier.
Proceedings of NIPS-03.
You can view the abstract or you can retrieve the paper.
Preference-based Constrained Optimization with CP-nets: Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, and David Poole
Computational Intelligence 20(2):137-157 (2004).
You can view the abstract or you can retrieve the paper.
CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements: Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, and David Poole
Journal of Artificial Intelligence Research (JAIR) 21:135-191 (2004).
Winner, 2009 IJCAI-JAIR Best Paper Prize
You can view the abstract or you can retrieve the paper.
Accelerating Reinforcement Learning through Implicit Imitation: Bob Price and Craig Boutilier.
Journal of Artificial Intelligence Research (JAIR) 19:569-629 (2003).
You can view the abstract or you can retrieve the paper.
Constraint-based Optimization with the Minimax Decision Criterion: Craig Boutilier, Pascal Poupart, Relu Patrascu, and Dale Schuurmans.
Ninth International Conference on Principles and Practice of Constraint Programming (CP2003), Kinsale, Ireland, pp.168--182 (2003).
You can view the abstract or you can retrieve the paper.
Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation: Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro and William E. Walsh.
Proceedings of the Nineteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-03), Acapulco, pp.89--97 (2003).
You can view the abstract or you can retrieve the paper.
Active Collaborative Filtering: Craig Boutilier, Richard S. Zemel and Benjamin Marlin.
Proceedings of the Nineteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-03), Acapulco, pp.98--106 (2003).
You can view the abstract or you can retrieve the paper.
On the Foundations of Expected Expected Utility: Craig Boutilier.
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, pp.285--290 (2003).
You can view the abstract or you can retrieve the paper.
Incremental Utility Elicitation with the Minimax Regret Decision Criterion: Tianhan Wang and Craig Boutilier.
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, pp.309--316 (2003).
You can view the abstract or you can retrieve the paper.
A Bayesian Approach to Imitation in Reinforcement Learning: Bob Price and Craig Boutilier.
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, pp.712--717 (2003).
You can view the abstract or you can retrieve the paper.
Coordination in Multiagent Reinforcement Learning: A Bayesian Approach: Georgios Chalkiadakis and Craig Boutilier.
Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-03), pp.709--716, Melbourne (2003).
You can view the abstract or you can retrieve the paper.
Online Queries for Collaborative Filtering: Craig Boutilier and Rich Zemel.
Appeared at AI-Stats 2003.
You can view the abstract or you can retrieve the paper.
Value-directed Compression of POMDPs: Pascal Poupart and Craig Boutilier.
Advances in Neural Information Processing Systems 15 (NIPS-2002), Vancouver, BC, pp.1547--1554 (2002).
You can view the abstract or you can retrieve the paper.
A POMDP Formulation of Preference Elicitation Problems: Craig Boutilier
Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), Edmonton, AB, pp.239--246 (2002).
You can view the abstract or you can retrieve the paper.
Solving Concisely Expressed Combinatorial Auction Problems: Craig Boutilier
Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), Edmonton, AB, pp.359--366 (2002).
You can view the abstract or you can retrieve the paper.
Piecewise Linear Value Function Approximation for Factored MDPs: Pascal Poupart, Craig Boutilier, Dale Schuurmans and Relu Patrascu.
Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), Edmonton, AB, pp.292--299 (2002).
You can view the abstract or you can retrieve the paper.
Greedy Linear Value Function Approximation for Factored Markov Decision Processes: Pascal Poupart, Relu Patrascu, Dale Schuurmans, Craig Boutilier, and Carlos Guestrin.
Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), Edmonton, AB, pp.285--291 (2002).
You can view the abstract or you can retrieve the paper.
Partial-order Planning with Concurrent Interacting Actions: Craig Boutilier and Ronen I. Brafman
Journal of AI Research (JAIR) 14, pp.105--136 (2001)
Retrieve the paper.
Bidding Languages for Combinatorial Auctions: Craig Boutilier and Holger H. Hoos
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), Seattle, pp.1211--1217 (2001).
You can view the abstract or you can retrieve the paper.
Symbolic Dynamic Programming for First-order MDPs: Craig Boutilier, Ray Reiter and Bob Price
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), Seattle, pp.690--697 (2001).
You can view the abstract or you can retrieve the paper.
UCP-Networks: A Directed Graphical Representation of Conditional Utilities: Craig Boutilier, Fahiem Bacchus and Ronen I. Brafman
Proceedings of the Seventeenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-01), Seattle, pp.56--64 (2001).
You can view the abstract or you can retrieve the paper.
Value-Directed Sampling Methods for Monitoring POMDPs: Pascal Poupart, Luis E. Ortiz and Craig Boutilier,
Proceedings of the Seventeenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-01), Seattle, pp.453--461 (2001).
You can view the abstract or you can retrieve the paper.
Vector-space Analysis of Belief-state Approximation for POMDPs: Pascal Poupart and Craig Boutilier,
Proceedings of the Seventeenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-01), Seattle, pp.445--452 (2001).
You can view the abstract or you can retrieve the paper.
Imitation and Reinforcement Learning in Agents with Heterogeneous Actions: Bob Price and Craig Boutilier
Proceedings 14th Biennial Conference of the Canadian Society for Computational Studies of Intelligence (AI 2001), Lecture Notes in Computer Science 2056, Springer-Verlag, Berlin, pp.111-120 (2001).
You can view the abstract or you can retrieve the paper.
APRICODD: Approximate Policy Construction Using Decision Diagrams: Robert St-Aubin, Jesse Hoey , and Craig Boutilier
Advances in Neural Information Processing Systems 13 (NIPS-2000), Denver, CO, pp.1089--1095 (2000).
You can view the abstract or you can retrieve the paper.
Stochastic Dynamic Programming with Factored Representations: Craig Boutilier, Richard Dearden and Moises Goldszmidt
Artificial Intelligence 121(1), pp.49--107 (2000).
You can view the abstract or you can retrieve the paper.
Decision-Theoretic, High-level Agent Programming in the Situation Calculus: Craig Boutilier, Ray Reiter, Mikhail Soutchanski and Sebastian Thrun
Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, pp.355--362 (2000).
You can view the abstract or you can retrieve the paper.
Solving Combinatorial Auctions using Stochastic Local Search: Holger H. Hoos and Craig Boutilier
Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, pp.22--29 (2000).
You can view the abstract or you can retrieve the paper.
Approximately Optimal Monitoring of Plan Preconditions: Craig Boutilier
Proceedings of the Sixteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, pp.54--62 (2000).
You can view the abstract or you can retrieve the paper.
Value-Directed Belief State Approximation for POMDPs: Pascal Poupart and Craig Boutilier
Proceedings of the Sixteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, pp.497--506 (2000).
You can view the abstract or you can retrieve the paper.
Sequential Optimality and Coordination in Multiagent Systems: Craig Boutilier
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, pp.478--485 (1999).
You can view the abstract or you can retrieve the paper.
Sequential Auctions for the Allocation of Resources with Complementarities: Craig Boutilier, Moises Goldszmidt and Bikash Sabata
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, pp.527--534 (1999).
You can view the abstract or you can retrieve the paper.
SPUDD: Stochastic Planning using Decision Diagrams: Jesse Hoey , Robert St-Aubin, Alan Hu and Craig Boutilier
Proceedings of the Fifteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, pp.279--288 (1999).
You can view the abstract or you can retrieve the paper.
Continuous Value Function Approximation for Sequential Bidding Policies: Craig Boutilier, Moises Goldszmidt and Bikash Sabata
Proceedings of the Fifteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, pp.81--90 (1999).
You can view the abstract or you can retrieve the paper.
Implicit Imitation in Multiagent Reinforcement Learning: Bob Price and Craig Boutilier
Proceedings of the Sixteenth International Conference on Machine Learning (ICML-99), Bled, Slovenia, pp.325--334 (1999).
You can view the abstract or you can retrieve the paper.
Reasoning With Conditional Ceteris Paribus Preference Statements: Craig Boutilier, Ronen I. Brafman, Holger H. Hoos and David Poole
Proceedings of the Fifteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, pp.71--80 (1999).
You can view the abstract or you can retrieve the paper.
Decision-Theoretic Planning: Structural Assumptions and Computational Leverage: Craig Boutilier, Thomas Dean and Steve Hanks
Journal of AI Research (JAIR) 11:1--94 (1999).
You can view the abstract or you can retrieve the paper.
This is a long (94 page) survey article that ties together a lot of recent work on decision-theoretic planning within the MDP framework and describes the relationship between many classical planning, decision theoretic planning, and MDP representations and algorithms. It also surveys several of the recent forms of abstraction, aggregation and decomposition that have been introduced in the DTP community.
A Unified Model of Qualitative Belief Change: A Dynamical Systems Perspective: Craig Boutilier,
Artificial Intelligence 98(1--2), pp.281--316 (1998).
You can view the abstract or you can retrieve the paper.
Belief Revision with Unreliable Observations: Craig Boutilier, Nir Friedman and Joseph Y. Halpern
Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), Madison, WI, pp.127--134 (1998).
You can view the abstract or you can retrieve the paper.
Hierarchical Solution of Markov Decision Processes using Macro-actions: Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling , Thomas Dean and Craig Boutilier,
Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), Madison, WI, pp.220--229 (1998).
You can view the abstract or you can retrieve the paper.
Solving Very Large Weakly Coupled Markov Decision Processes: Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas Dean and Craig Boutilier
Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), Madison, WI, pp.165--172 (1998).
You can view the abstract or you can retrieve the paper.
Structured Reachability Analysis for Markov Decision Processes: Craig Boutilier, Ronen I. Brafman and Christopher Geib
Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), Madison, WI, pp.24--32 (1998).
You can view the abstract or you can retrieve the paper.
LPSP: A Linear Plan-level Stochastic Planner: Ronen I. Brafman, Holger H. Hoos and Craig Boutilier
17th Workshop of the UK Planning and Scheduling Special Interest Group, West York, UK
You can view the abstract or you can retrieve the paper.
The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems: Caroline Claus and Craig Boutilier,
Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), Madison, WI, pp.746--752 (1998).
You can view the abstract or you can retrieve the paper.
An earlier and rather different version appeared in the AAAI Workshop on Multiagent Learning, 1997. This earlier version contains material on partial action observability, not present in the latter (which contains material on optimistic exploration methods that increase the probability of converging to optimal equilibria not contained in the earlier version). You can view the abstract or you can retrieve the earlier version of the paper.
AIJ Editorial: Economic Principles of Multi-Agent Systems: Craig Boutilier, Yoav Shoham and Michael P. Wellman,
Artificial Intelligence Journal 94(1):1-6 (1997).
You can retrieve the paper.
Abstraction and Approximate Decision Theoretic Planning: Richard Dearden and Craig Boutilier
Artificial Intelligence 89(1):219-283 (1997).
You can view the abstract or you can retrieve the paper.
Prioritized Goal Decomposition of Markov Decision Processes: Toward a Synthesis of Classical and Decision Theoretic Planning: Craig Boutilier, Ronen I. Brafman and Christopher Geib,
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), Nagoya, pp.1156--1163 (1997).
You can view the abstract or you can retrieve the paper.
Structured Solution Methods for Non-Markovian Decision Processes: Fahiem Bacchus, Craig Boutilier and Adam Grove
Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), Providence, RI, pp.112--117 (1997).
You can view the abstract or you can retrieve the paper.
Planning with Concurrent Interacting Actions: Craig Boutilier and Ronen I. Brafman,
Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), Providence, RI, pp.720--729 (1997).
You can view the abstract or you can retrieve the paper.
Structured Arc Reversal and Simulation of Dynamic Probabilistic Networks: Adrian Y. W. Cheuk and Craig Boutilier ,
Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI-97), Providence, RI, pp.72--79 (1997).
You can view the abstract or you can retrieve the paper.
Correlated Action Effects in Decision Theoretic Regression: Craig Boutilier ,
Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI-97), Providence, RI, pp.30--37 (1997).
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A Constraint-Based Approach to Preference Elicitation and Decision Making: Craig Boutilier, Ronen I. Brafman Christopher Geib and David Poole
AAAI Spring Symposium on Qualitative Decision Theory, Stanford, CA, pp.19--28 (1997).
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Abduction to Plausible Causes: An Event-based Model of Belief Update: Craig Boutilier
Artificial Intelligence Journal 83(1):143-166 (1996).
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Iterated Revision and Minimal Change of Conditional Beliefs: Craig Boutilier
Journal of Philosophical Logic 25(3):262-305 (1996).
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Context-Specific Independence in Bayesian Networks: Craig Boutilier, Nir Friedman, Moises Goldszmidt and Daphne Koller
Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI-96), Portland, OR, pp.115--123 (1996).
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Learning Conventions in Multiagent Stochastic Domains using Likelihood Estimates: Craig Boutilier
Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI-96), Portland, OR, pp.106--114 (1996).
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Rewarding Behaviors: Fahiem Bacchus, Craig Boutilier and Adam Grove
Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, OR, pp.1160--1167 (1996).
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Approximating Value Trees in Structured Dynamic Programming: Craig Boutilier and Richard Dearden
Proceedings of the Thirteenth International Conference on Machine Learning (ML-96), Bari, IT, pp.54--62 (1996).
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Computing Optimal Policies for Partially Observable Decision Processes using Compact Representations: Craig Boutilier and David Poole
Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, OR, pp.1168--1175 (1996).
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Planning, Learning and Coordination in Multiagent Decision Processes: Craig Boutilier
Sixth Conference on Theoretical Aspects of Rationality and Knowledge (TARK-96), Amsterdam, pp.195--210 (1996).
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The Frame Problem and Bayesian Network Action Representations: Craig Boutilier and Moises Goldszmidt
Proceedings of the Eleventh Biennial Canadian Conference on Artificial Intelligence (AI '96), Toronto, pp.69--83 (1996).
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Abduction as Belief Revision: Craig Boutilier and Veronica Becher
Artificial Intelligence Journal 77(1):43-94 (1995).
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Exploiting Structure in Policy Construction: Craig Boutilier, Richard Dearden and Moises Goldszmidt
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), Montreal, pp.1104--1111 (1995). (See also AAAI Spring Symposium on Extending Theories of Action, Stanford, March 1995).
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Process-Oriented Planning and Average-Reward Optimality: Craig Boutilier and Martin L. Puterman
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), Montreal, pp.1096--1103 (1995).
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Generalized Update: Belief Change in Dynamic Settings: Craig Boutilier
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), Montreal, pp.1550--1556 (1995).
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Planning Under Uncertainty: Structural Assumptions and Computational Leverage: Craig Boutilier, Thomas Dean and Steve Hanks
Unpublished Manuscript (version to appear in Proc. 3rd European Workshop on Planning (EWSP'95), Assisi, Italy, September, 1995).
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Nondeterministic Actions and the Frame Problem: Craig Boutilier and Nir Friedman
Proceedings of the AAAI Spring Symposium on Extending Theories of Action: Formal Theories and Practical Applications, Stanford, CA, pp.39-44 (1995).
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On the Revision of Probabilistic Belief States: Craig Boutilier
Notre Dame Journal of Formal Logic 36(1):158-183 (1995).
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Toward a Logic for Qualitative Decision Theory: Craig Boutilier
Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR-94), Bonn, pp.75-86 (1994)
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Due to a number of requests, and after much searching for the Postscript (so I wouldn't have to reconstruct the whole thing), I've added this paper to my page.
Unifying Default Reasoning and Belief Revision in A Modal Framework: Craig Boutilier
Artificial Intelligence Journal 68(1):33-85 (1994).
Conditional Logics of Normality: A Modal Approach: Craig Boutilier
Artificial Intelligence Journal 68(1):87-154 (1994).
Modal Logics for Qualitative Possibility Theory: Craig Boutilier
International Journal of Approximate Reasoning 10(2):173-201 (1994).
Using Abstractions for Decision-Theoretic Planning with Time Constraints: Craig Boutilier and Richard Dearden
Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, pp.1016-1022 (1994).
Integrating Planning and Execution in Stochastic Domains: Richard Dearden and Craig Boutilier
Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI-94), Seattle, pp.162-194 (1994).
An Event-Based Abductive Model of Update: Craig Boutilier
Proceedings of the Tenth Biennial Canadian Conference on Artificial Intelligence (AI-94), Banff, AB, pp.241-248 (1994).
On the Semantics of Stable Inheritance Reasoning: Craig Boutilier
Computational Intelligence 9(1):pp.73-110 (1993).
Revision Sequences and Nested Conditionals: Craig Boutilier
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93), Chambery, France, pp.519-525 (1993).
Abduction as Belief Revision: A Model of Preferred Explanation: Craig Boutilier and Veronica Becher
Proceedings of the Eleventh National Conference on Artificial Intelligence (AAAI-93), Washington, D.C., pp.649-654 (1993).
Revision by Conditional Beliefs: Craig Boutilier and Moises Goldszmidt
Proceedings of the Eleventh National Conference on Artificial Intelligence (AAAI-93), Washington, D.C., pp.649-654 (1993).
The Probability of a Possibility: Adding Uncertainty to Default Rules: Craig Boutilier
Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (UAI-93), Washington, D.C., pp.461-468 (1993).
A Modal Characterization of Defeasible Deontic Conditionals and Conditional Goals: Craig Boutilier
Proceedings of the AAAI Spring Symposium on Reasoning About Mental States: Formal Theories and Applications, Stanford, CA, pp.30-39 (1993).
Epistemic Entrenchment in Autoepistemic Logic: Craig Boutilier
Fundamenta Informaticae 17(1-2):5-30 (1992).
A Logic for Revision and Subjunctive Queries: Craig Boutilier
Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), San Jose, pp.609-615 (1992).
Normative, Subjunctive and Autoepistemic Defaults: Adopting the Ramsey Test: Craig Boutilier
Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR-92), Cambridge, pp.685-696 (1992).
Modal Logics for Qualitative Possibility and Beliefs: Craig Boutilier
Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence (UAI-92), Stanford, pp.17-24 (1992).
What is a Default Priority?: Craig Boutilier
Proceedings of the Ninth Biennial Canadian Conference on Artificial Intelligence (AI-92), Vancouver, pp.140-147 (1992).
Inaccessible Worlds and Irrelevance: Preliminary Report: Craig Boutilier
Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI-91), Sydney, pp.413-418 (1991).
Conditional Logics of Normality as Modal Logics: Craig Boutilier
Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), Boston, pp.594-599 (1990).
A Semantical Approach to Stable Inheritance Reasoning: Craig Boutilier
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), Detroit, pp.1134-1139 (1989).

By: Craig Boutilier (Google+)