Thomas L. Dean Adjunct Professor of Computer Science

Tom Dean is Professor of Computer Science and Cognitive and Linguistic Sciences at Brown University. He received his B.A. in mathematics from Virginia Polytechnic Institute & State University in 1982 and his M.Sc. and Ph.D. in computer science from Yale University in 1984 and 1986 respectively. His research interests include automated planning and control, computational biology, machine learning, neural modeling, probabilistic inference, robotics and spatial and temporal reasoning.

Dean served as the Deputy Provost of Brown University from 2003 to 2005, as the chair of Brown's Computer Science Department from 1997 until 2002, and as the Acting Vice President for Computing and Information Services from 2001 until 2002. He is a fellow of AAAI, a member of the Academic Alliance of the National Center for Women and Information Technology and a former member of the IJCAI Inc. Board of Trustees. He has served on the Executive Council of AAAI and the Computing Research Association Board of Directors. He was a recipient of an NSF Presidential Young Investigator Award in 1989. He served as program co-chair for the 1991 National Conference on Artificial Intelligence and the program chair for the 1999 International Joint Conference on Artificial Intelligence held in Stockholm.

Dean is co-author with Mike Wellman of the Morgan-Kaufmann text entitled Planning and Control which ties together techniques from artificial intelligence, operations research, control theory, and the decision sciences. He is co-author with James Allen and John Aloimonos of Artificial Intelligence: Theory and Practice, an introductory text in Artificial Intelligence. His latest book Talking With Computers is published by Cambridge University Press and examines a wide range of topics from digital logic and machine language to artificial intelligence and searching the web.

Brown Affiliations

Research Areas

scholarly work

Exploiting Locality in Searching the Web (with Joel Young), Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico, 2003.

Solving Factored MDPs Using Non-Homogeneous Partitions (with Kee-Eung Kim), Artificial Intelligence 147 (2003).

Equivalence Notions and Model Minimization in Markov Decision Processes (with Robert Givan and Matthew Greig), Artificial Intelligence 147 (2003).

Solving Factored MDPs with Large Action Space Using Algebraic Decision Diagrams (with Kee-Eung Kim), Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence, Tokyo, Japan, 2002.

Solving Factored MDPs using Non-Homogeneous Partitions (with Kee-Eung Kim), Proceedings of the 17th International Joint Conference on Artificial Intelligence, Seattle, Washington, 2001.

Bounded-parameter Markov Decision Processes (with Robert Givan and Sonia Leach), Artificial Intelligence 122 (2000).

Approximate Solutions to Factored Markov Decision Processes via Greedy Search in the Space of Finite State Controllers (with Kee-Eung Kim and Nicolas Meuleau), Fifth International Conference on Artificial Intelligence in Planning Systems, Colorado, 2000.

Decision Theoretic Planning: Structural Assumptions and Computational Leverage (with Craig Boutilier and Steve Hanks), Journal of Artificial Intelligence Research 11 (1999).

Hierarchical solution of Markov decision processes using macro-actions (with Milos Hauskrecht, Nicolas Meuleau, Craig Boutilier, Leslie Kaelbling), Proceedings of the 1998 Conference on Uncertainty in Artificial Intelligence, Madison, Wisconsin, 1998.

Solving very large weakly coupled Markov decision processes (with Craig Boutilier, Milos Hauskrecht, Leslie Kaelbling, Kee-Eung Kim, Leonid Peshkin, and Nicolas Meuleau), Proceedings of the 15th National Conference on Artificial Intelligence, Madison, Wisconsin, 1998.

Solving Planning Problems with Large State and Action Spaces (with Robert Givan and Kee-Eung Kim), Fourth International Conference on Artificial Intelligence in Planning Systems, Pittsburgh, Pennsylvania, 1998.

A Conditional Scheduling Approach to Designing Real-Time Systems (with Lloyd Greenwald), Fourth International Conference on Artificial Intelligence in Planning Systems, Pittsburgh, Pennsylvania, 1998.

Bounded Parameter Markov Decision Processes (with Robert Givan and Sonia Leach), Fourth European Conference on Planning, Toulouse, France, 1997.

Model Minimization, Regression, and Propositional STRIPS Planning (with Robert Givan), Proceedings of the 15th International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.

Model Minimization in Markov Decision Processes (with Robert Givan), Proceedings of the 14th National Conference on Artificial Intelligence, Providence, Rhode Island, 1997.

A Retrospective on the AAAI Robot Competitions (with R. Peter Bonasso), AI Magazine, 1997.

Coping With Uncertainty in Map Learning (with Kenneth Basye and Jeffrey Scott Vitter), Machine Learning 29 (1997).

Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes (with Robert Givan and Sonia Leach), Proceedings of the 1997 Conference on Uncertainty in Artificial Intelligence, Providence, Rhode Island, 1997.

Challenge Problems for Artificial Intelligence (with Bart Selman, Rodney Brooks, Eric Horvitz, Tom Mitchell and Nils Nilsson), Proceedings of the 13th National Conference on Artificial Intelligence, Portland, Oregon, 1996.

Strategic Directions in Artificial Intelligence (with Jon Doyle), ACM Computing Surveys 28 (1996), reprinted in the AI Magazine 18 (1997).

Localized Temporal Reasoning Using Subgoals and Abstract Events (with Shieu-Hong Lin), Journal of Computational Intelligence 12 (1996).

A Framework for the Development of Multi-Agent Architectures (with Moises Lejter), IEEE Expert 11 (1996).

Package Routing in Transportation Networks with Fixed Vehicle Schedules: Formulation, Complexity Results and Approximation Algorithms (with Lloyd Greenwald) Networks 27 (1996).

Generating Optimal Policies for High-Level Plans with Conditional Branches and Loops (with Shieu-Hong Lin), Third European Conference on Planning, Assisi, Italy, 1995.

Planning Under Uncertainty: Structural Assumptions and Computational Leverage (with Craig Boutilier and Steve Hanks), Third European Conference on Planning, Assisi, Italy, 1995.

On the Complexity of Solving Markov Decision Problems (with Michael Littman and Leslie Kaelbling), Proceedings of the 1995 Conference on Uncertainty in Artificial Intelligence, Montreal, Quebec, 1995.

Planning Under Time Constraints in Stochastic Domains (with Leslie Kaelbling, Jak Kirman, and Ann Nicholson), Artificial Intelligence 76 (1995).

Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning (with Dana Angluin, Kenneth Basye, Sean Engelson, Leslie Kaelbling, Evangelos Kokkevis, and Oded Maron), Journal of Machine Learning 18 (1995).

Learning Dynamics: System Identification for Perceptually Challenged Agents (with Kenneth Basye and Leslie Kaelbling), Artificial Intelligence 72 (1995).

Decomposition Techniques for Planning in Stochastic Domains (with Shieu-Hong Lin), Proceedings of the 14th International Joint Conference on Artificial Intelligence, Montreal, Quebec, 1995.

Practical Probabilistic Diagnostic Systems: Decision Support Systems for Real-World Applications (with Adnan Darwiche and Eric Horvitz), a video produced for AAAI with support from Rockwell International, 1995.

Solving Time-Critical Decision Making in Stochastic Domains (with Lloyd Greenwald), Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, Washington, 1994.

Solving Time-Critical Decision-Making Problems with Predictable Computational Demands (with Lloyd Greenwald), Proceedings of the Second International Conference on AI Planning Systems, Chicago, Illinois 1994.

Anticipating Computational Demands when Solving Time-Critical Decision-Making Problems (with Lloyd Greeenwald), Proceedings of the Workshop on the Algorithmic Foundations of Robotics, San Francisco, California, 1994.

Decision-Theoretic Deliberation Scheduling for Problem Solving in Time-Constrained Environments (with Mark Boddy), Artificial Intelligence 67 (1994).

Localized Temporal Reasoning: A State-Based Approach (with Shieu-Hong Lin), Proceedings of TIME-94: An International Workshop on Temporal Representation and Reasoning, Pensacola Beach, Florida, 1994.

Exploiting Locality in Temporal Reasoning (with Shieu-Hong Lin), Second European Conference on Planning, Vadstena, Sweden, 1993.

Using Goals to Find Plans with High Expected Utility (with Jak Kirman, Ann Nicholson, Moises Lejter and Eugene Santos Jr.) Second European Conference on Planning, Vadstena, Sweden, 1993.

Deliberation Scheduling for Time-Critical Sequential Decision Making (with Leslie Kaelbling, Jak Kirman and Ann Nicholson), 1993 Conference on Uncertainty in Artificial Intelligence, Washington, D.C., 1993.

Planning with Deadlines in Stochastic Domains (with Leslie Kaelbling, Jak Kirman and Ann Nicholson), Proceedings of the Eleventh National Conference on Artificial Intelligence, Washington, D.C., 1993.

Planning and Selective Perception for Mobile Robot Object Retrieval Tasks (with Ted Camus and Jon Monsarrat), Proceedings of the DARPA Image Understanding Workshop, Washington, D.C., 1993.

1992 AAAI Robot Exhibition and Competition (with R. Peter Bonasso), AI Magazine, Spring 1993.

Anticipating Tomorrow's Technology Needs, Omni Magazine, November, 1992.

Robot Map-Learning as Learning Labeled Graphs from Noisy Data (with Kenneth Basye and Leslie Kaelbling), Proceedings of the Seventh Yale Workshop on Adaptive and Learning Systems, New Haven, CT, 1992.

Probabilistic Network Representations of Continuous-Time Stochastic Processes for Applications in Planning and Control (with Jak Kirman and Keiji Kanazawa), (extended abstract) Proceedings of the First International Conference on AI Planning Systems, College Park, Maryland, 1992.

Representation Issues in Bayesian Decision Theory for Planning and Active Perception (with Jak Kirman), Proceedings of the DARPA Image Understanding Workshop, San Diego, California, 1992.

Vision and Robotics Research at Brown (with David Cooper and William Wolovich), Proceedings of the DARPA Image Understanding Workshop, San Diego, California, 1992.

A Decision-Theoretic Approach to Planning, Perception and Control (with Kenneth Basye and Jak Kirman), IEEE Expert 7 (1992).

Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning (with Dana Angluin, Kenneth Basye, Sean Engelson, Leslie Kaelbling, Evangelos Kokkevis,and Oded Maron), Proceedings of the Tenth National Conference on Artificial Intelligence, San Jose, California, 1992.

Sensor Abstractions for Control of Navigation (with Kenneth Basye and Jak Kirman), Proceedings of the 1991 IEEE International Conference on Robotics and Automation, Sacramento, California, 1991.

Decision-Theoretic Control of Inference for Time-Critical Applications, International Journal of Intelligent Systems 6 (1991).

Planning and Active Perception (with Kenneth Basye and Moises Lejter), Proceedings of the 1990 DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control (also appears in ``Autonomous Mobile Robots: Control, Planning, and Architecture'' (IEEE Computer Society Press), edited by S. S. Iyengar and Alberto Elfes).

Image Understanding Research at Brown (with David Cooper and William Wolovich), Proceedings of the DARPA Image Understanding Workshop, Pittsburgh, Pennsylvania, 1990.

Sequential Decision Making for Active Perception (with Theodore Camus and Jak Kirman), Proceedings of the DARPA Image Understanding Workshop, Pittsburgh, Pennsylvania, 1990.

Knowledge Representations for Learning Control (with Chuck Anderson, Mieczyslaw M. Kokar, Kimon Valavanis, and Wlodek Zadrozny), Proceedings of the Fifth IEEE International Symposium on Intelligent Control, Philadelphia, Pennsylvania, 1990.

Prediction, Observation, and Estimation in Planning and Control (with Keiji Kanazawa and John Shewchuk), Proceedings of the Fifth IEEE International Symposium on Intelligent Control, Philadelphia, Pennsylvania, 1990.

An Approach to Reasoning About Continuous Change for Applications in Planning (with Greg Siegle), Proceedings of the Eighth National Conference on Artificial Intelligence, Cambridge, Massachusetts, 1990.

Coping with Uncertainty in a Control System for Navigation and Exploration (with Kenneth Basye, Robert Chekaluk, Seungseok Hyun, Moises Lejter, Margaret Randazza), Proceedings of the Eighth National Conference on Artificial Intelligence, Cambridge, Massachusetts, 1990.

Toward Learning Time-Varying Functions With High Input Dimensionality (with John Shewchuk), Proceedings of the Fifth IEEE International Symposium on Intelligent Control, Philadelphia, Pennsylvania, 1990.

Planning Under Uncertainty and Time Pressure, Proceedings of the 1990 DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control, San Diego, California, 1990.

Solving Time-Dependent Planning Problems (with Mark Boddy), Proceedings of the 11th International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989.

Coping With Uncertainty in Map Learning (with Kenneth Basye and Jeffrey Scott Vitter), Proceedings of the 11th International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989 (also appears in ``Autonomous Mobile Robots: Perception, Mapping, and Navigation'' (IEEE Computer Society Press), edited by S. S. Iyengar and Alberto Elfes).

Map Learning with Indistinguishable Locations (with Kenneth Basye), Proceedings of the Conference on Telerobotics sponsored by the Jet Propulsion Laboratory, Pasadena, California, 1989 (a revised version of this paper also appears in the Proceedings of the Fifth Workshop on Uncertainty in Artificial Intelligence, Windsor, Ontario, 1989, and in ``Uncertainty in Artificial Intelligence 5'' (Elsevier Science Publishers), edited by M. Henrion, J. Lemmer, and L. N. Kanal)).

Approximation Algorithms for Planning and Control (with Mark Boddy), Proceedings of the Conference on Telerobotics sponsored by the Jet Propulsion Laboratory, Pasadena, California, 1989.

A Model for Reasoning About Persistence and Causation (with Keiji Kanazawa), Journal of Computational Intelligence 5 (1989).

Using Temporal Hierarchies to Efficiently Maintain Large Temporal Databases, Journal of the Association for Computing Machinery 36 (1989).

Persistence and Probabilistic Inference (with Keiji Kanazawa), IEEE Transactions on Systems, Man, and Cybernetics 19 (1989).

A Model for Projection and Action (with Keiji Kanazawa), Proceedings of the 11th International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989.

On the Value of Goals (with Mike Wellman), Proceedings of the 1988 Rochester Planning Workshop, Rochester, New York, 1988.

Locating a Mobile Robot Using Local Observations and a Global Satellite Map (with Akira Hayashi), Proceedings of Third IEEE International Symposium on Intelligent Control, Washington, DC, 1988 (a revised version of this paper also appears in the Proceedings of the Conference on Telerobotics sponsored by the Jet Propulsion Laboratory, Pasadena, California, 1989, under the title ``Satellite-Map Position Estimation for the Mars Rover'').

Reasoning About Indistinguishable Locations (with Moises Lejter), Proceedings of SPIE Conference on Intelligent Robots and Computer Vision, Cambridge, Massachusetts, 1988.

Probabilistic Temporal Reasoning (with Keiji Kanazawa), Proceedings of the Seventh National Conference on Artificial Intelligence, St. Paul, Minnesota, 1988.

An Analysis of Time-Dependent Planning (with Mark Boddy), Proceedings of the Seventh National Conference on Artificial Intelligence, St. Paul, Minnesota, 1988.

Probabilistic Causal Reasoning (with Keiji Kanazawa), Proceedings of the Canadian Society for Computational Studies of Intelligence, Edmonton, Alberta, 1988 (a revised version of this paper also appears in the Proceedings of the Fourth Workshop on Uncertainty in Artificial Intelligence, St. Paul, Minnesota, 1988, and in ``Uncertainty in Artificial Intelligence 4'' (Elsevier Science Publishers), edited by R. Shachter, T .S. Levitt, J. Lemmer, and L. N. Kanal).

Planning Paradigms, AI Magazine, Fall 1988 (also appears in the Proceedings of the DARPA Knowledge-Based Planning Workshop, Austin, Texas, 1987, and in the Proceedings of the Third Annual Workshop of Israeli Association for Artificial Intelligence, Tel Aviv, Israel, December 1987).

Hierarchical Planning Involving Deadlines, Travel Time, and Resources (with James Firby and David Miller), Journal of Computational Intelligence 4 (1988) (also appears in ``Readings in Planning'' (Morgan Kaufmann), edited by James Allen, James Hendler, and Austin Tate, and in ``Autonomous Mobile Robots: Control, Planning, and Architecture'' (IEEE Computer Society Press), edited by S. S. Iyengar and Alberto Elfes).

Reasoning About Partially Ordered Events (with Mark Boddy), Artificial Intelligence 36 (1988) (also appears in ``Readings in Qualitative Reasoning About Physical Systems'' (Morgan Kaufmann), edited by Dan Weld and Johan De Kleer).

An Approach to Reasoning About the Effects of Actions for Automated Planning Systems, Annals of Operations Research 12 (1988).

On the Complexity of Integrating Spatial Measurements, Proceedings of SPIE Conference on Intelligent Robots and Computer Vision, Cambridge, Massachusetts, 1988.

Planning, Execution, and Control, Proceedings of the DARPA Knowledge-Based Planning Workshop, Austin, Texas, 1987.

High-Level Planning and Low-Level Control, Proceedings of SPIE Conference on Intelligent Robots and Computer Vision, Cambridge, Massachusetts, 1987.

Large Temporal Data Bases, Proceedings of the 10th International Joint Conference on Artificial Intelligence, Milan, Italy, 1987.

Prediction and Causal Reasoning in Planning (with Mark Boddy), Proceedings of the Workshop on Telerobotics sponsored by the Jet Propulsion Laboratory, Pasadena, California, 1987.

Temporal Data Base Management (with Drew McDermott), Artificial Intelligence 32 (1987) (also appears in ``Readings in Planning'' (Morgan Kaufmann), edited by James Allen, James Hendler, and Austin Tate).

Incremental Causal Reasoning (with Mark Boddy), Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, Washington, 1987.

Decision Support for Coordinated Multi-Agent Planning, Proceedings of the Third International ACM Conference on Office Information Systems, Providence, Rhode Island, 1986.

Handling Shared Resources in a Temporal Data Base Management System, Decision Support Systems 2 (1986).

Temporal Notation and Causal Terminology (with Yoav Shoham), Proceedings of the Seventh Annual Conference of the Cognitive Science Society, Irvine, California, 1985.

Deadlines, Travel Time, and Robot Problem Solving (with James Firby and David Miller), Proceedings of the 9th International Joint Conference on Artificial Intelligence, Los Angeles, California, 1985.

Efficient Robot Planning with Deadlines and Travel Time (with James Firby and David Miller), Proceedings of the 6th International Symposium on Robotics and Automation, Santa Barbara, California, 1985.

Temporal Reasoning Involving Counterfactuals and Disjunctions, Proceedings of the 9th International Joint Conference on Artificial Intelligence, Los Angeles, California, 1985.

Planning and Temporal Reasoning under Uncertainty, Proceedings of the IEEE Workshop on Principles of Knowledge-Based Systems, Denver, Colorado, 1984.

Managing Time Maps, Proceedings of the Canadian Society for Computational Studies of Intelligence, London, Ontario, 1984.

Publications [Conferences]

research overview

Thomas Dean's general research interests include automated temporal and spatial reasoning, planning, robotics, learning, and probabilistic inference. He is particularly interested in problems in which the notions of uncertainty and risk are complicated by the imposition of a limited time for deliberation and action. The basic tools for his research are derived from probability, statistics, Bayesian decision theory, and the design and analysis of algorithms. The applications involve mobile robots that perform such tasks as search and rescue, as well as disembodied "knowbots" that operate on the World Wide Web.

research statement

Thomas Dean's general research interests include automated temporal and spatial reasoning, planning, robotics, learning, and probabilistic inference. He is particularly interested in problems in which the notions of uncertainty and risk are complicated by the imposition of a limited time for deliberation and action. When the problems faced by an agent in a dynamic environment are complex, one typically must trade time for precision in making decisions: How long should you spend deciding what to pack when rushing to catch a plane? A similar tradeoff arises in deciding how much time and effort to expend in learning about a new or evolving environment: When visiting a new city, how much effort should you put into learning the streets and landmarks?


A more recent project involves building a probabilistic model of the neocortex. The basic tools for his research are derived from probability, statistics, Bayesian decision theory, and the design and analysis of algorithms. The applications involve mobile robots that perform such tasks as search and rescue, as well as and disembodied "knowbots" that operate on the World Wide Web.

funded research

Statistical Models of the Primate Neocortex: Implementation and Application (PI), National Science Foundation, $479,999, 11/15/2005 - 10/31/2008

Implementing A Computational Model of the Cortex (PI), Brown Brain Science Research Program, $4,000, 11/2005

Bootstrapping Cognitive Systems with Implicit Semantic Knowledge (PI), Defense Advanced Research Projects Agency (DARPA), $84,153, 12/01/2005 - 11/30/2006

Stochastic Models for Web Agents and the Web Environment (PI), Defense Advanced Research Projects Agency (DARPA), $550,000, 6/29/2000 - 9/28/2002

Time-Critical Planning and Scheduling for Aircraft Maintenance and Deployment (Supplement) (PI), Defense Advanced Research Projects Agency (DARPA), $40,000, 6/1/1999 - 5/31/2000

Model Acquisition for Markov Decision Problems (PI), Air Force Office of Scientific Research, $116,600, 12/1/1996 - 11/3/1997

Time-Critical Planning and Scheduling for Aircraft Maintenance and Deployment (PI), Defense Advanced Research Projects Agency (DARPA), $924,461, 6/1/1995 - 5/31/1998

Robot Planning, Learning and Selective Perception in Stochastic Domains (PI), National Science Foundation, $150,000, 6/1/1994 - 5/31/1997

National Virtual Laboratories (PI), National Science Foundation, $50,000, 6/1/1994 - 5/31/1995

Distributed Planning and Control for Applications in Transportation Scheduling (PI), Defense Advanced Research Projects Agency (DARPA), $912,500, 6/1/1991 - 5/31/1994

High-Performance Design Environments (Co-PI), Defense Advanced Research Projects Agency (DARPA)/Office of Naval Research, $2,580,000, 1991-1996

Studies in Integrated Planning and Control (PI), IBM, $75,000, 1/1/1990 - 12/31/1990

Image Understaning for Service Robots (PI), NSF/DARPA Initiative IRIS/CISE, $690,000, 9/1/1989 - 8/30/1992

Perception for Planning and Control (PI), AT&T Foundation, $20,000, 9/1/1989 - 8/30/1990

Presidential Investigator Award (PI), National Science Foundation, $125,000, 8/1/1989 - 12/31/1994

A Mobile Sensor Platform for Research in Planning and Control (PI), AT&T Foundation, $25,000, 9/1/1988 - 8/30/1989

High-Level Planning and Low-Level Control (PI), Defense Advanced Research Projects Agency (DARPA), $440,000, 9/1/1988 - 8/30/1991

Multiparadigm Design Environments (Co-PI), National Science Foundation, $3,504,831, 1988-1993

Temporal Inference Systems (PI), Jet Propulsion Laboratory, $30,000, 9/1/1987 - 8/31/1988

Time-Dependent Planning (PI), National Science Foundation, $133,758, 3/1/1987 - 2/28/1989

Faculty Development Award (PI), IBM, $60,000, 7/1/1986 - 6/30/1988

Scalable Inference and Learning in Very Large Graphical; Models Patterned After the Primate Visual Cortex (PI), Office of Naval Research, 793152, 7/1/2006-12-31/2006