AI publications involving people at Brown

2000

• Don Blaheta and Eugene Charniak, ``Assigning Function Tags to Parsed Text'', Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics, pp. 234--240, Seattle, WA, 2000. Postscript (7 pages/143K), PDF (7 pages/170K); Abstract.
• Eugene Charniak, ``A Maximum-Entropy-Inspired Parser'', Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics, pp. 132--139, Seattle, WA, 2000.
• Thomas Hofmann and Keith Hall, ``Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval'', Proceedings of the Seventeenth International Conference on Machine Learning, 2000. Postscript (8 pages/250K).
• Milos Hauskrecht and Hamish Fraser, ``Planning treatment of ischemic heart disease with partially observable Markov decision processes'', Artificial Intelligence in Medicine, vol. 18, pp. 221-244, 2000.
• Milos Hauskrecht, Luis Ortiz, Ioannis Tsochantaridis, and Eli Upfal, ``Computing global strategies for multi-market commodity trading'', Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, pp. 159--166, 2000. Postscript (8 Pages/329K).
• Thomas Hofmann, ``Learning the Similarity of Documents'', Advances in Neural Information Processing Systems, MIT Press 2000. Postscript (7 Pages/144K), PDF (7 Pages/160K).
• Luis E. Ortiz and Leslie Pack Kaelbling, ``Adaptive Importance Sampling for Estimation in Structured Domains'', Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, 2000. Postscript (9 pages/315K).
• Luis E. Ortiz and Leslie Pack Kaelbling, ``Sampling Methods for Action Selection in Influence Diagrams'', Proceedings of the Seventeenth National Conference on Artificial Intelligence, 2000. Postscript (8 pages/279K).
• Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, and Leslie Pack Kaelbling, ``Learning to Cooperate via Policy Search'', Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, 2000. Postscript (8 pages), Abstract.
• William D. Smart and Leslie Pack Kaelbling, ``Practical Reinforcement Learning in Continuous Spaces'', to appear in Proceedings of the Seventeenth International Conference on Machine Learning, Stanford, CA, 2000. Postscript (7 pages/330K), Abstract.

1999

• Matthew Berland, Eugene Charniak, ``Finding Parts in Very Large Corpora'', Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 1999. Postscript (8 pages/162K), Abstract.
• Don Blaheta and Eugene Charniak, ``Automatic Compensation for Parser Figure-of-Merit Flaws'', Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 1999. Postscript (6 pages/195K), PDF (6 pages/154K); Abstract.
• David Meir Blei and Leslie Pack Kaelbling, ``Shortest Paths in a Dynamic Uncertain Domain'', IJCAI Workshop on Adaptive Spatial Representations of Dynamic Environments, 1999. Postscript (7 pages/669K).
• Craig Boutilier, Tom Dean, and Steve Hanks, ``Decision Theoretic Planning: Structural Assumptions and Computational Leverage'', Journal of Artificial Intelligence Research, Volume 11, Pages 1--94, 1999. Postscript (94 pages/1.3M).
• Sharon A. Caraballo, ``Automatic construction of a hypernym-labeled noun hierarchy from text'', Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 1999. Postscript (7 pages/254K).
• Sharon A. Caraballo and Eugene Charniak, ``Determining the Specificity of Nouns from Text'', Proceedings of the 1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, 1999. Postscript (8 pages/276K).
• Milos Hauskrecht, Gopal Pandurangan, and Eli Upfal. ``Computing near optimal strategies for stochastic investment planning problems'', Proceedings of the 16th International Joint Conference on Artificial Intelligence, pp. 1310-1315, 1999. Postscript (6 pages/125K).
• Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, and Leslie Pack Kaelbling, ``Learning Finite-State Controllers for Partially Observable Environments'', Proceedings of the Fifteenth International Conference on Uncertainty in Artificial Intelligence, 1999. Postscript (10 pages/182K).
• Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, and Anthony R. Cassandra, ``Solving POMDPs by Searching the Space of Finite Policies'', Proceedings of the Fifteenth International Conference on Uncertainty in Artificial Intelligence, 1999. Postscript (10 pages/154K).
• Luis E. Ortiz and Leslie Pack Kaelbling, ``Accelerating EM: An Empirical Study'', Proceedings of the Fifteenth International Conference on Uncertainty in Artificial Intelligence, 1999. Postscript (10 pages/499K).
• Leonid Peshkin, Mikhail S. Gelfand, ``Segmentation of Yeast DNA Using Hidden Markov Models'', Bioinformatics, 15:12, pp. 980--986, Oxford University Press, 1999. Postscript (8 pages/174K), Abstract.
• Leonid Peshkin, Nicolas Meuleau, and Leslie Pack Kaelbling, ``Learning Policies with External Memory'', Proceedings of the Sixteenth International Conference on Machine Learning, 1999. Postscript (8 pages/233K).
• Hagit Shatkay, ``Learning Hidden Markov Models with Geometrical Constraints'', Proceedings of the Fifteenth International Conference on Uncertainty In Artificial Intelligence, 1999. Postscript (10 pages/547K).

1998

• Sharon Caraballo and Eugene Charniak, ``New figures of merit for best-first probabilistic chart parsing'', Computational Linguistics, Volume 24, Number 2, pp. 275-298, June 1998. Postscript (31 pages/411K).
• Eugene Charniak, ``Statistical techniques for natural language parsing'', AI Magazine. To appear. Postscript (18 pages/165K); Abstract.
• Eugene Charniak, Sharon Goldwater, and Mark Johnson, ``Edge-Based Best-First Chart Parsing'', 6th Workshop for Very Large Corpora, 1998. Postscript (7 pages/151K).
• Thomas Dean, Robert Givan and Kee-Eung Kim, ``Solving Planning Problems with Large State and Action Spaces'', Fourth International Conference on Artificial Intelligence in Planning Systems. Pittsburgh, PA, 1998. Postscript (9 pages/307K).
• Andrew P. Duchon, William H. Warren, and Leslie Pack Kaelbling, ``Ecological Robotics'', Adaptive Behavior, Volume 6, Number 3/4, 1998. Postscript (30 pages/1.6M).
• Niyu Ge, John Hale, and Eugene Charniak, ``A Statistical Approach to Anaphora Resolution'', 6th Workshop for Very Large Corpora, 1998. Postscript (10 pages/175K).
• Lloyd Greenwald and Thomas Dean, ``A Conditional Scheduling Approach to Designing Real-Time Systems'', Fourth International Conference on Artificial Intelligence in Planning Systems. Pittsburgh, PA, 1998. Postscript (8 pages/438K).
• Milos Hauskrecht and Hamish Fraser, ``Modeling Treatment of Ischemic Heart Disease with Partially Observable Markov Decision Processes'', Proceedings of the American Medical Informatics Association annual symposium on Computer Applications in Health Care, Orlando, Florida, pp. 538-542, 1998. Postscript (5 pages/98K), PDF (5 pages/85K).
• Milos Hauskrecht and Hamish Fraser, ``Planning medical therapy using partially observable Markov decision processes'', Proceedings of the 9th International Workshop on Principles of Diagnosis (DX-98), Cape Cod, MA, pp. 182-189, 1998. Postscript (8 pages/160K).
• Milos Hauskrecht, Nicolas Meuleau, Craig Boutilier, Leslie Pack Kaelbling, and Thomas Dean, ``Hierarchical Solution of Markov Decision Processes Using Macro-Actions'', Proceedings of the Fourteenth International Conference on Uncertainty In Artificial Intelligence, 1998. Postscript (10 pages/268K).
• Leslie Pack Kaelbling, Learning in Embedded Systems. Talk given at the Smithsonian Institute, Washington D.C., 1998. Postscript (47 slides/2.9M)
• Leslie Pack Kaelbling, Michael L. Littman and Anthony R. Cassandra, ``Planning and Acting in Partially Observable Stochastic Domains'', Artificial Intelligence. To appear. Postscript (45 pages/1.3M).
• Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas Dean, and Craig Boutilier, ``Solving Very Large Weakly Coupled Markov Decision Processes'', Proceedings of the Fifteenth National Conference on Artificial Intelligence, 1998. Postscript (8 pages/187K).
• Brian Roark and Eugene Charniak, ``Noun-phrase co-occurrence statistics for semi-automatic semantic lexicon construction'', 36th Annual Meeting of the Association for Computational Linguistics, pp. 1110--1116, Montreal, Québec, 2000. Postscript (7 pages/222K).
• Hagit Shatkay and Leslie Pack Kaelbling, ``Heading in the Right Direction,'' Proceedings of the 15th International Conference on Machine Learning, 1998. Postscript (9 pages/396K).

1997

• Kenneth Basye, Thomas Dean, and Jeffrey Scott Vitter, ``Coping With Uncertainty in Map Learning'', Machine Learning Journal, Volume 29, 1997. Postscript (journal) (31 pages/291K); Postscript (conference) (6 pages/141K); Abstract.
• Eugene Charniak, ``Statistical parsing with a context-free grammar and word statistics'', Proceedings of the Fourteenth National Conference on Artificial Intelligence. AAAI Press/MIT Press, Menlo Park (1997). Postscript (6 pages/129K); Abstract.
• Thomas Dean, Algebraic Structure of Sequential Decision Machines. A talk presented at AT&T on November 12, 1997. Postscript (33 slides/353K).
• Thomas Dean and Robert Givan, ``Model Minimization in Markov Decision Processes'', AAAI97. Postscript (6 pages/313K).
• Thomas Dean, Robert Givan, and Sonia Leach, ``Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes'', CUAI97. Postscript (8 pages/419K).
• Robert Givan and Thomas Dean, ``Model Minimization, Regression, and Propositional STRIPS Planning'', IJCAI97. Postscript (6 pages/308K); Postscript (16 slides/158K).
• Robert Givan, Sonia Leach, and Thomas Dean, ``Bounded Parameter Markov Decision Processes, ECP97. Postscript (13 pages/278K); Postscript (15 slides/146K).
• Leslie Pack Kaelbling, Why Robbie Can't Learn: The Difficulty of Learning in Autonomous Agents. A talk given as the IJCAI Computers and Thought Address, Nagoya, Japan, 1997. Compressed postscript (59 slides/646K).
• Hagit Shatkay and Leslie Pack Kaelbling, ``Learning Topological Maps with Weak Local Odometric Information,'' Proceedings of the 17th International Joint Conference on Artificial Intelligence, 1997. Postscript (8 pages/360K).
• Hagit Shatkay and Leslie Pack Kaelbling, ``Learning Hidden Markov Models with Geometric Information'', Technical Report cs-97-04, Department of Computer Science, Brown University, 1997.

1996

• Sharon A. Caraballo and Eugene Charniak, ``Figures of Merit for Best-First Probabilistic Chart Parsing'', Proceedings of the Conference on Empirical Methods in Natural Language Processing, 1996, pp. 127-132. Philadelphia, PA. HTML (tech report) (1K/164K).
• Eugene Charniak, ``Tree-bank grammars'', Technical Report CS-96-02. Department of Computer Science, Brown University, 1996. Compressed postscript (12 pages/148K); Abstract.
• Thomas Dean and Subbarao Kambhampati, ``Planning and Scheduling'', CRC Handbook of Computer Science and Engineering, 1996. Postscript (40 pages/456K).
• Jon Doyle and Thomas Dean, ``Strategic Directions in Artificial Intelligence'', ACM Computing Surveys, Volume 28, Number 4, December, 1996. HTML (81K).
• Murat Ersan and Eugene Charniak, ``A statistical syntactic disambiguation program and what it learns'', TR CS-95-29. Brown University, Department of Computer Science, 1996. Also Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, S. Wermter, E. Riloff, and G. Scheler, eds. New York: Springer, 1996. Compressed postscript (18 pages/167K); Abstract.
• Lloyd Greenwald and Thomas Dean, ``Package Routing in Transportation Networks with Fixed Vehicle Schedules: Formulation, Complexity Results and Approximation Algorithms'', Networks, Volume 27, Pages 81-93, 1996. Postscript (22 pages/438K).
• Leslie Pack Kaelbling, Anthony R. Cassandra, and James A. Kurien, ``Acting Under Uncertainty: Discrete Bayesian Models for Mobile-Robot Navigation'', Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1996. Postscript (9 pages/431K).
• Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore, ``Reinforcement Learning: A Survey'', Journal of Artificial Intelligence Research, Volume 4, 1996. Postscript (40 pages/878K); HTML (9K/631K).
• Moises Lejter and Thomas Dean, ``A Framework for the Development of Multi-Agent Architectures'', by Moises Lejter and Thomas Dean, IEEE Expert, Volume 11, 1996. Postscript (48 pages/518K).
• Shieu-Hong Lin and Thomas Dean, ``Localized Temporal Reasoning Using Subgoals and Abstract Events'', Computational Intelligence, Volume 12, Number 3, Pages 423-449, 1996. Postscript (29 pages/578K); Abstract.

1995

• Kenneth Basye, Thomas Dean and Leslie Kaelbling, ``Learning Dynamics: System Identification for Perceptually Challenged Agents'', Artificial Intelligence, Volume 72, Pages 139-171, 1995. Postscript (46 pages/1.3M); Abstract.
• Craig Boutilier, Thomas Dean, and Steve Hanks, ``Planning Under Uncertainty: Structural Assumptions and Computational Leverage'', EWSP95. Abstract.
• Eugene Charniak, ``Parsing with context-free grammars and word statistics'', Technical Report CS-95-28. Department of Computer Science, Brown University, 1995. Compressed postscript (19 pages/208K); Abstract.
• Thomas Dean, James Allen, and Yiannis Aloimonos, Artificial Intelligence: Theory and Practice Benjamin Cummings, 1995.
• Thomas Dean, Dana Angluin, Kenneth Basye, Sean Engelson, Leslie Kaelbling, Evangelos Kokkevis, and Oded Maron, ``Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning'', Machine Learning Journal, Volume 18, Number 1, Pages 81-108, 1995. Postscript (36 pages/641K); Abstract.
• Thomas Dean, Leslie Pack Kaelbling, Jak Kirman, and Ann Nicholson, ``Planning Under Time Constraints in Stochastic Domains'', Artificial Intelligence, Volume 76, Number 1-2, Pages 35-74, 1995. Postscript (journal) (53 pages/672K); Postscript (conference) (6 pages/289K); Abstract.
• Thomas Dean and Shieu-Hong Lin, ``Decomposition Techniques for Planning in Stochastic Domains'', IJCAI95. Postscript (7 pages/430K); Abstract; Technical report.
• Andrew P. Duchon, William H. Warren, and Leslie Pack Kaelbling, ``Controlling Behavior with Optical Flow'', Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society, 1995. Postscript (6 pages/1.3M).
• Lloyd Greenwald and Thomas Dean, ``Anticipating Computational Demands when Solving Time-Critical Decision-Making Problems'', The Algorithmic Foundations of Robotics, ed. K. Goldberg, D. Halperin, J.C. Latombe, and R. Wilson. A. K. Peters, Boston, MA, 1995. Postscript (18 pages/478K).
• Leslie Pack Kaelbling, Reinforcement Learning: The Good, the Bad, and the Ugly. A rant given at the 2nd European Workshop on Reinforcement Learning. Postscript (26 slides/89K).
• Leslie Pack Kaelbling with Michael L. Littman and Anthony R. Cassandra, Partially Observable Markov Decision Processes for AI. A talk given in 1995. Postscript (44 slides/278K).
• Shieu-Hong Lin and Thomas Dean, ``Generating Optimal Policies for Markov Decision Processes Formulated as Plans with Conditional Branches and Loops'', EWSP95. Postscript (14 pages/379K); Abstract.
• Michael L. Littman, Anthony R. Cassandra, and Leslie Pack Kaelbling, ``Learning Policies for Partially Observable Environments: Scaling Up'', Proceedings of the Twelfth International Conference on Machine Learning, 1995. Postscript (9 pages/315K).
• Michael Littman, Thomas Dean, and Leslie Kaelbling, ``On the Complexity of Solving Markov Decision Problems'', CUAI95. Postscript (9 pages/256K).
• Stanley J. Rosenschein and Leslie Pack Kaelbling, ``A Situated View of Representation and Control'', Artificial Intelligence, Vol. 73, 1995. Postscript (25 pages/324K).

1994

• Mark Boddy and Thomas Dean, ``Decision-Theoretic Deliberation Scheduling for Problem Solving in Time-Constrained Environments'', Artificial Intelligence, Volume 67, Number 2, Pages 245-286, 1994. Postscript (51 pages/509K); Abstract.
• Anthony R. Cassandra, Leslie Pack Kaelbling, and Michael L. Littman, ``Acting Optimally in Partially Observable Stochastic Domains'', Proceedings of the Twelfth National Conference on Artificial Intelligence, 1994. Postscript (6 pages/392K).
• Eugene Charniak, Glenn Carroll, John Adcock, Antony Cassandra, Yoshihiko Gotoh, Jeremy Katz, Michael Littman, and John McCann, ``Taggers for parsers'', Artificial Intelligence. To appear. Postscript (17 pages/196K); Abstract; Compressed postscript (tech report) (14 pages/140K).
• Thomas Dean, Decision Theoretic Planning and Markov Decision Processes. a tutorial presented at the Summer Institute on Probability and Artificial Intelligence, Corvalis, Oregon, 1994. Postscript (overview) (31 pages/356K); Postscript (slides, lecture 1) (30 slides/201K); Abstract (lecture 1); Postscript (slides, lecture 2) (25 slides/250K); Abstract (lecture 2).
• Lloyd Greenwald and Thomas Dean, ``Monte Carlo Simulation and Bottleneck-Centered Heuristics for Time-Critical Scheduling in Stochastic Domains'', Proceedings of ARPA/Rome Lab Workshop on Planning and Scheduling, 1994. Postscript (12 pages/240K).
• Lloyd Greenwald and Thomas Dean, ``Solving Time-Critical Decision-Making Problems with Predictable Computational Demands'', Proceedings of the Second International Conference on AI Planning Systems, 1994. Postscript (6 pages/344K).
• Leslie Pack Kaelbling, ``Associative Reinforcement Learning: Functions in k-DNF'', Machine Learning, Vol. 15, Number 3, 1994. Postscript (20 pages/237K).
• Leslie Pack Kaelbling, ``Associative Reinforcement Learning: A Generate and Test Algorithm'', Machine Learning, Vol. 15, Number 3, 1994. Postscript (20 pages/255K).
• Leslie Pack Kaelbling, Markov Decision Processes as a Foundation for Intelligent Agents. A talk given at AAAI94. Postscript (40 slides/206K).
• Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore, Tutorial on Reinforcement Learning. A talk given at AAAI94. Postscript (132 slides/1.0M).
• Jak Kirman, Ann Nicholson, Moises Lejter, Thomas Dean, and Eugene Santos Jr., ``Using Goals to Find Plans with High Expected Utility'', Current Trends in AI Planning, ed. E. Sandewall and C. Backstrom. IOS Press, Amsterdam, 1994. Postscript (13 pages/2.0M).
• Shieu-Hong Lin and Thomas Dean, ``Exploiting Locality in Temporal Reasoning'', Current Trends in AI Planning, ed. E. Sandewall and C. Backstrom. IOS Press, Amsterdam, 1994. Postscript (14 pages/252K).

1993

• Eugene Charniak, Statistical Language Learning. Cambridge: MIT Press, 1993.
• Eugene Charniak, Curtis Hendrickson, Neil Jacobson, and Mike Perkowitz, ``Equations for part-of-speech tagging'', Proceedings of the Eleventh National Conference on Artificial Intelligence. Menlo Park: AAAI Press/MIT Press, 1993, pp. 784-789. Postscript (6 pages/144K); Abstract.
• Leslie Pack Kaelbling, ``Hierarchical Reinforcement Learning: Preliminary Results'', Proceedings of the Tenth International Conference on Machine Learning, 1993.
• Leslie Pack Kaelbling, Learning in Embedded Systems. The MIT Press, 1993.
• Leslie Pack Kaelbling, ``Learning to Achieve Goals'', Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, 1993. Postscript (5 pages/181K).

1992

• Kenneth Basye, Thomas Dean, Jak Kirman, and Moises Lejter, ``Decision-Theoretic Approach to Planning, Perception, and Control'', IEEE Expert, Volume 7, Number 4, Pages 58-65, 1992. Postscript (33 pages/427K); Abstract.
• Thomas Dean, Kenneth Basye, and Leslie Kaelbling, ``Uncertainty in Graph-based Map Learning'', Robot Learning, ed. Jonathon Connell and Sridhar Mahadevan. Kluwer, 1992. Postscript (23 pages/340K); Abstract.
• Thomas Dean, Kenneth Basye, and John Shewchuk, ``Reinforcement Learning for Planning and Control'', Machine Learning Methods for Planning and Scheduling, ed. Steve Minton. Morgan Kaufmann, 1992. Postscript (20 pages/184K); Abstract.
• Thomas Dean and Lloyd Greenwald, ``A Formal Description of the Distributed Transportation Problem'', Brown University Department of Computer Science Technical Report CS-92-14, 1992.

1991

• Thomas Dean and Michael Wellman, Planning and Control. Morgan Kaufmann, 1991. This book addresses the problem of controlling the behavior of an agent embedded in a dynamic environment. The treatment ties together techniques from artificial intelligence, operations research, control theory, and the decision sciences.
• Leslie Pack Kaelbling and Stanley J. Rosenschein, ``Action and Planning in Embedded Agents'', in Robotics and Autonomous Systems, Vol. 6, No. 1; also in Designing Autonomous Agents, P. Maes, editor. The MIT Press, 1991.

1987

• Eugene Charniak¸ Chris Riesbeck, Drew McDermott, and James Meehan, Artificial Intelligence Programming, 2nd ed. Hillsdale NJ: Lawrence Erlbaum Associates, 1987. (1st ed. 1980)

1985

• Eugene Charniak and Drew McDermott, Introduction to Artificial Intelligence. Reading MA: Addison-Wesley, 1985.

1976

• Eugene Charniak and Yorick Wilks, Computational Semantics. Amsterdam: North-Holland, 1976.