A. G. Barto's Publications

Following is a list of A.G. Barto's publications in reverse chronological order. Many of the recent references have links that allow you access to that publication. Links associated with a particular reference (e.g., conference) were current at the time of publication. Click here for a comprehensive listing of all publications of the Autonomous Learning Laboratory.

To jump to a specific year:
| 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1996 | 1995 | 1994 | before 1994 |



    2013

  • Barto, A., Mirolli, M., and Baldasarre, G. (to appear)
    Novelty or surprise?
    Frontiers in Cognitive Science.

  • Shah, A., Fagg, A., and Barto, A. (2013)
    A Dual Process Account of Coarticulation in Motor Skill Acquisition
    Journal of Motor Behavior, vol. 45, pages 531-549.
    [ DOI link] [PubMed link]

  • Neikum, S., Osentoski, S., Chitta, B., Marthi, B., and Barto, A. (2013)
    Incremental Semantically Grounded Learning from Demonstration
    Robotics: Science and Systems IX, Berlin, Germany.
    [ pdf ] [ video ]

  • Barto, A. (2013)
    Intrinsic Motivation and Reinforcement Learning
    In G. Baldassarre and M. Mirolli, editors, Intrinsically Motivated Learning in Natural and Artificial Systems, pages 17-47, Springer.

  • Kuindersma, S.R., Grupen, R.A., and Barto, A.G. (2013)
    Variable Risk Control via Stochastic Optimization
    International Journal of Robotics Research, vol. 32, pages 806-825.
    [pdf]

  • Konidaris, G., Kuindersma, S., Niekum, S., Grupen, R., and Barto, A. (2013)
    Robot Learning: Some Recent Examples
    Proceedings of the Sixteenth Yale Workshop on Adaptive and Learning Systems, Center for Systems Science, Department of Electrical Engineering, Yale University, pages 71-76.
    [ pdf ]


    2012

  • Kuindersma, S., Grupen, R., and Barto, A. (2012)
    Variational Bayesian Optimization for Runtime Risk-Sensitive Control
    Robotics: Science and Systems VIII (RSS), MIT Press, Cambridge MA, pages 201-208.
    Best Spotlight Talk and E-poster Award.
    [pdf]

  • Niekum, S., Osentoski, S., Konidaris, G.D., and Barto, A.G. (2012)
    Learning and Generalization of Complex Tasks from Unstructured Demonstrations
    Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012, pages 5239-5246.
    [ pdf ] [ video ]

  • Thomas, P.S., and Barto, A.G. (2012)
    Motor Primitive Discovery
    Proceedings of the IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), pages 1-8.
    [ pdf ]

  • Castro da Silva, B., Konidaris, G.D., and Barto, A.G. (2012)
    Learning Parameterized Skills
    Proceedings of the Twenty Ninth International Conference on Machine Learning, pages 1679-1686.
    [pdf]

  • Kuindersma, S., Grupen, R., and Barto, A. (2012)
    Variable Risk Dynamic Mobile Manipulation
    RSS 2012 Workshop on Mobile Manipulation, Sydney, NSW, Australia.
    [pdf]

  • Konidaris, G.D., Scheidwasser, I., and Barto, A.G. (2012)
    Transfer in Reinforcement Learning via Shared Features
    Journal of Machine Learning Research, vol. 13, pages 1333-1371.
    [pdf]

  • Konidaris, G., Kuindersma, S., Grupen, R., and Barto, A. (2012)
    Robot Learning from Demonstration by Constructing Skill Trees
    The International Journal of Robotics Research, vol. 31, No. 3, pages 360-375.
    [ freely accessible draft ]


    2011

  • Ribas-Fernandes, J., Solway, A., Diuk, C., Barto, A.G., Niv, Y., and Botvinick, M.M. (2011)
    A Neural Signature of Hierarchical Reinforcement Learning
    Neuron, vol. 71, pages 370-379.
    [ pdf ]

  • Kuindersma, S., Grupen, R., and Barto, A. (2011)
    Learning Dynamic Arm Motions for Postural Recovery
    Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots. Bled, Slovenia.
    [ pdf ] [ video ]

  • Konidaris, G.D., Kuindersma, S.R., Grupen, R.A., and Barto, A.G. (2011)
    Autonomous Skill Acquisition on a Mobile Manipulator
    Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI-11), pages 1468-1473. San Francisco, CA.
    [ pdf ] [ video ]

  • Niekum, S., and Barto, G. (2011)
    Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery
    Advances in Neural Information Processing Systems 24 (NIPS-11). Granada, Spain.
    [ pdf ]

  • Thomas, P.S. and Barto, A.G. (2011)
    Conjugate Markov Decision Processes
    Proceedings of the Twenty-Eighth International Conference on Machine Learning, (ICML-11), pages 137-144.
    [ pdf ]

  • Konidaris, G.D., Kuindersma, S.R., Grupen, R.A., and Barto, A.G. (2011)
    Acquiring Transferrable Mobile Manipulation Skills
    Robotics and System Science (RSS) 2011 Workshop on Mobile Manipulation: Learning to Manipulate, Los Angles, CA.
    [ pdf ]

  • Konidaris, G.D., Kuindersma, S.R., Grupen, R.A., and Barto, A.G. (2011)
    CST: Constructing Skill Trees by Demonstration
    Proceedings of the ICML Workshop on New Developments in Imitation Learning, Bellevue, WA.
    [ pdf ]

  • Barto, A.G., Singh, S., and Lewis, R.L. (2011)
    Intrinsically Motivated Machines
    Proceedings of the Fifteenth Yale Workshop on Adaptive and Learning Systems, Center for Systems Science, Department of Electrical Engineering, Yale University, pages 123-129.
    [ pdf ]


    2010

  • Diuk, C., Botvinick, M., Barto, A., and Niv, Y. (2010)
    Hierarchical Reinforcement Learning: An fMRI Study of Learning in a Two-Level Gambling Task
    Society for Neuroscience Meeting 2010 (SfN 2010).
    [ pdf ]

  • Barto, A.G. (2010)
    What are Intrinsic Reward Signals?
    One-page commentary for the AMD (Autonomous Mental Development) Newsletter, IEEE Computational Intelligence Society, volume 7, no. 2.
    [ pdf ]

  • Kuindersma, S., Konidaris, G., Grupen, R., and Barto, A. (2010)
    Learning from a Single Demonstration: Motion Planning with Skill Segmentation
    Poster Abstract. NIPS Workshop on Learning and Planning in Batch Time Series Data. Whistler, BC.
    [ pdf ]

  • Konidaris, G., Kuindersma, S., Barto, A., and Grupen, R. (2010)
    Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories
    In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta (Eds.), Advances in Neural Information Processing Systems 23 (NIPS '10), pages 1162-1170.
    [ pdf ]

  • Vigorito, C.M. and Barto, A.G. (2010)
    Intrinsically Motivated Hierarchical Skill Learning in Structured Environments
    IEEE Transactions on Autonomous Mental Development (IEEE TAMD). Volume 2, Issue 2, pages 83-90.
    [ pdf ]

  • Singh, S., Lewis, R.L., Barto, A.G., and Sorg, J. (2010)
    Instrinsically Motivated Reinforcement Learning: An Evolutionary Perspective
    IEEE Transactions on Autonomous Mental Development (IEEE TAMD). Volume 2, Issue 2, pages 70-82.
    [pdf]

  • Niekum, S., Barto, A.G., and Spector, L. (2010)
    Genetic Programming for Reward Function Search
    IEEE Transactions on Autonomous Mental Development (IEEE TAMD). Volume 2, Issue 2, pages 132-143.


    2009

  • Konidaris, G.D. and Barto, A.G. (2009)
    Skill Discovery in Continuous Reinforcement Learning Domains Using Skill Chaining
    In Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams and A. Culotta (Eds.), Advances in Neural Information Processing Systems 22 (NIPS '09), pages 1015-1023.
    [ pdf ]

  • Vigorito, C.M. and Barto, A.G. (2009)
    Incremental Structure Learning in Factored MDPs with Continuous States and Actions
    Technical Report UM-CS-2009-029, Department of Computer Science, University of Massachusetts at Amherst.
    [ pdf ]

  • Singh, S., Lewis, R.L., and Barto A.G.(2009)
    Where Do Rewards Come From?
    In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pages 2601-2606. Austin, TX.
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2009)
    Towards the Autonomous Acquisition of Robot Skill Hierarchies (poster abstract)
    In the Robotics: Science and Systems Workshop on Bridging the Gap Between High-Level Discrete Representations and Low-Level Continuous Behaviors (RSS Workshop), Seattle, WA, June 2009.
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2009)
    Efficient Skill Learning Using Abstraction Selection
    Proceedings of the Twenty First International Joint Conference on Artificial Intelligence (IJCAI '09), July 14-17, Pasadena, CA.
    [ pdf ]

  • Botvinick, M.M., Niv, Y., and Barto, A.G. (2009)
    Hierarchically Organized Behavior and its Neural Foundations: A Reinforcement-Learning Perspective
    Cognition, vol. 113 (special issue on Reinforcement Learning and Higher Cognition, edited by Michael Frank and Nathaniel Daw), pages 262-280.
    [ pdf ]

  • Shah, A. and Barto, A.G. (2009)
    Effect on Movement Selection of an Evolving Sensory Representation: A Multiple Controller Model of Skill Acquisition
    Brain Research, vol. 1299 (special issue on Computational Cognitive Neuroscience II, edited by Sue Becker and Nathaniel Daw), pages 55-73.
    [ pdf ]


    2008

  • Şimşek, Ö. and Barto, A.G. (2008)
    Skill Characterization Based on Betweenness
    Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS-08), December 8-11, Vancouver, B.C., Canada.
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2008)
    Sensorimotor Abstraction Selection for Efficient, Autonomous Robot Skill Acquisition
    Proceedings of the 7th IEEE International Conference on Development and Learning (ICDL-08), August 9 - 12, Monterey, CA
    [ pdf ]

  • Vigorito, C.M. and Barto, A.G. (2008)
    Autonomous Hierarchical Skill Acquisition in Factored MDPs
    Proceedings of The Fourteenth Yale Workshop on Adaptive and Learning Systems, June 2 - 4, New Haven, CT
    [ pdf ]

  • Vigorito, C.M. and Barto, A.G. (2008)
    Hierarchical Representations of Behavior for Efficient Creative Search
    AAAI Spring Symposium on Creative Intelligent Systems, March 26 - 28, Palo Alto, CA
    [ pdf ] [ poster ]


    2007

  • Jonsson, A. and Barto, A.G. (2007)
    Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
    Proceedings of the Seventh Symposium on Abstraction, Reformulation, and Approximation (SARA 2007), Whistler, British Columbia, Canada, July 18 - 21, 2007.
    Also published as Miguel, I. and Tuml, W. (editors) Lecture Notes in Artificial Intelligence: Abstraction, Reformulation, and Approximation, vol. 4612, pages 273-284, Springer, New York, NY, USA.
    [ pdf ]

  • Barto, A.G. (2007)
    Temporal Difference Learning
    Scholarpedia, 2(11):1604
    [ pdf ]

  • Shah, A., and Barto, A.G. (2007)
    Effect on Movement Selection of Evolving Sensory Representation
    poster presented at the Third Annual Computational Cognitive Neuroscience Conference (CCNC07), in conjunction with Dynamical Neuroscience XV, November, San Diego, CA.
    [ pdf ]

  • Shah, A., and Barto, A.G. (2007)
    Functional Mechanisms of Motor Skill Acquisition
    poster presented at the Sixteenth Annual Computational Neuroscience Meeting (CNS*2007), July 7th - 12th, Toronto, Ontario, Canada. Abstract published in BMC Neuroscience 2007, 8(Suppl 2):P203 (6 July 2007)
    [ abstract | pdf of poster ]

  • Arroyo, I., Ferguson, K., Johns, J., Dragon, T., Meheranian, H., Fisher, D., Barto, A.G., Mahadevan, S., and Woolf, B. (2007)
    Repairing Disengagement with Non-Invasive Interventions
    Proceedings of the 13th International Conference of Artificial Intelligence in Education (AIED-07)
    [ pdf ]

  • Vigorito, C., Ganesan, D., and Barto, A.G. (2007)
    Adaptive Control of Duty-Cycling in Energy-Harvesting Wireless Sensor Networks
    Proceedings of the Fourth Annual IEEE Communications Society Conference on Sensor, Mesh, and Ad Hoc Communications and Networks (SECON-07), San Diego, CA.
    [ pdf ] (Note: this recieved the best paper award)

  • Şimşek, Ö. and Barto, A.G. (2007)
    Betweenness Centrality as a Basis for Forming Skills
    University of Massachusetts, Department of Computer Science Technical Report TR-2007-26, 2007
    [ pdf ]

  • Barringer, C.W. and Barto, A.G. (2007)
    Discrete Submovements Using Predictive Models
    poster presented at Neural Control of Movement Conference, March 25-30, Seville, Spain
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2007)
    Building Portable Options: Skill Transfer in Reinforcement Learning
    Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07), Hyderabad, India, January 6-12, 2007.
    [ pdf ]

      NOTE: an earlier version appeared as a 2006 tech report: Konidaris, G.D. and Barto, A.G. (2006), Building Portable Options: Skill Transfer in Reinforcement Learning, University of Massachusetts Department of Computer Science Technical Report UM-CS-2006-17, March, 2006 [ pdf ]




    2006

  • Jonsson, A. and Barto, A.G. (2006)
    Causal Graph based decomposition of factored MDPs
    Journal of Machine Learning Research, vol 7, pages 2259-2301, Nov., 2006.
    [ pdf ]

  • Ferguson, K., Arroyo, A., Mahadevan, S., Woolf, B., and Barto, A.G. (2006)
    Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels
    Proceedings of the Eighth International Conference on Intelligent Tutoring Systems (ITS-06), Jhongli, Taiwan, June 26 - 30, 2006
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2006)
    An Adaptive Robot Motivational System
    Animals to Animats 9: Proceedings of the 9th International Conference on Simulation of Adaptive Behavior (SAB-06), CNR, Roma, Italy, September 25 - 29, 2006.
    [ pdf ]

  • Konidaris, G.D. and Barto, A.G. (2006)
    Building Portable Options: Skill Transfer in Reinforcement Learning
    University of Massachusetts Department of Computer Science Technical Report UM-CS-2006-17, March, 2006
    [ pdf ]

  • Wolfe, A.P. and Barto, A.G. (2006)
    Decision Tree Methods for Finding Reusable MDP Homomorphisms
    Proceedings of The 21st National Conference on Artificial Intelligence (AAAI-06), Boston, MA, July 16 - 20, 2006
    [ pdf ]

  • Wolfe, A.P. and Barto, A.G. (2006)
    Defining Object Types and Options Using MDP Homomorphisms
    Proceedings of the ICML-06 Workshop on Structural Knowledge Transfer for Machine Learning, Pittsburgh, PA, June, 2006
    [ pdf paper | pdf slides ]

  • Shah, A., Barto, A.G., and Fagg, A.H. (2006)
    Biologically-Based Functional Mechanisms of Coarticulation
    poster presented at Neural Control of Movement Conference, May 2-7, 2006, Key Biscayne, FL
    [ pdf ]

  • Şimşek, Ö. and Barto, A.G. (2006)
    An Intrinsic Reward Mechanism for Efficient Exploration
    Proceedings of the Twenty-Third International Conference on Machine Learning (ICML 06), Pittsburgh, PA, June, 2006
    [
    pdf ]


    2005

  • Konidaris, G.D. and Barto, A.G. (2005)
    Autoshaping: Learning to Predict Reward for Novel States
    University of Masschusetts Department of Computer Science Technical Report UM-CS-2005-58, September, 2005
    [ ps.gz ]

  • Stout, A., Konidaris, G.D., and Barto, A.G. (2005)
    Intrinsically Motivated Reinforcement Learning: A Promising Framework For Developmental Robot Learning
    Proceedings of the AAAI Spring Symposium on Developmental Robotics, Stanford University, Stanford, CA, March 21-23, 2005.
    [ pdf ]

  • Jonsson, A. and Barto, A.G. (2005)
    A Causal Approach to Hierarchical Decomposition of Factored MDPs
    Proceedings of the Twenty-Second International Conference on Machine Learning ICML 05, Bonn, Germany, August 7-13
    [ pdf | ps ]

  • Jonsson, A., Johns, J., Mehranian, H., Arroyo, I., Woolf, B., Barto, A.G., Fisher, D., and Mahadevan, S.(2005)
    Evaluating the Feasibility of Learning Student Models from Data
    AAAI Workshop on Educational Data Mining, Pittsburgh, PA, July 9, 2005
    [ ps ]

  • Şimşek, O., Wolfe, A.P., and Barto, A.G. (2005)
    Identifying Useful Subgoals in Reinforcement Learning by Local Graph Partitioning
    Proceedings of the Twenty-Second International Conference on Machine Learning ICML 05, Bonn, Germany, August 7-13
    [ pdf | bibtex ]

  • Berthier, N. E., Rosenstein, M. T., and Barto, A. G. (2005)
    Approximate Optimal Control as a Model for Motor Learning
    Psychological Review vol. 112, pages 329 - 346

  • Barto, A.G. and Şimşek, O. (2005)
    Intrinsic Motivation for Reinforcement Learning Systems.
    Proceedings of the Thirteenth Yale Workshop on Adaptive and Learning Systems, pages 113-118. Center for Systems Science, Dunham Laboratory, Yale University, New Haven CT
    [ pdf ]


    2004

  • Singh, S., Barto, A.G., and Chentanez, N. (2004)
    Intrinsically Motivated Reinforcement Learning
    18th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, December 2004
    [ pdf ] NOTE: This and the preceding paper discuss different aspects of the same idea, with this paper focusing on algorithm specifics.

  • Barto, A.G., Singh, S., and Chentanez, N. (2004)
    Intrinsically Motivated Learning of Hierarchical Collections of Skills
    International Conference on Developmental Learning (ICDL), LaJolla, CA, USA
    [ pdf ] NOTE: This and the next paper discuss different aspects of the same idea, with this paper focusing on multi-disciplinary background.

  • Şimşek, Ö., Wolfe, A.P., and Barto, A.G. (2004)
    Local Graph Partitioning as a Basis for Generating Temporally-Extended Actions in Reinforcement Learning
    Proceedings of the AAAI-04 Workshop on Learning and Planning in Markov Processes - Advances and Challenges 2004.
    [ ps | pdf | bibtex ] NOTE: an improved version appeared as a technical report: [ pdf | ps ]

  • Si. J., Barto, A. G., Powell, W. B., Wunch D., editors. (2004)
    Handbook of Learning and Approximate Dynamic Programming Wiley-IEEE Press, Piscataway, NJ.

  • Barto, A.G., and Dietterich, T.G. (2004)
    Reinforcement Learning and Its Relationship to Supervised Learning
    In Si, J., Barto, A.G., Powell, W.B., and Wunsch, D., editors, Handbook of Learning and Approximate Dynamic Programming, Chapter 2, pages 47 - 64. Wiley-IEEE Press, Piscataway, NJ.

  • Barto, A.G., and Rosenstein, M.T. (2004)
    Supervised Actor-Critic Reinforcement Learning
    In Si, J., Barto, A.G., Powell, W.B., and Wunsch, D., editors, Handbook of Learning and Approximate Dynamic Programming, Chapter 14, pages 359 - 380. Wiley-IEEE Press, Piscataway, NJ.

  • Şimşek, Ö. and Barto, A.G. (2004)
    Using Relative Novelty to Identify Useful Temporal Abstractions in Reinforcement Learning
    Proceedings of theTwenty-First International Conference on Machine Learning (ICML 2004).
    [ ps | pdf | bibtex]

  • Shah, A., Fagg, A. H., and Barto, A. G. (2004)
    Cortical Involvement in the Recruitment of Wrist Muscles
    Journal of Neurophysiology vol. 91, pages 2445 - 2456
    [ pdf | ps | JNP pdf]


    2003

  • Barto, A. G. and Mahadevan, S. (2003)
    Recent Advances in Hierarchical Reinforcement Learning
    Discrete Event Dynamic Systems vol. 13(4), pages 341 - 379
    [ pdf ] NOTE: A preliminary unedited version of this paper was incorrectly published as part of Volume 13, Numbers 1/2, April 2003, in the Special Issue on Learning, Optimization, and Decision Making, Guest Edited by Xi-Ren Cao. The citation given above is for the true and correct paper. This pdf is not the true and correct version. It was provided to give you an idea of the paper, but for the official version please go through the journal. Thanks.

  • Ravindran, B. and Barto, A. G. (2003)
    Relativized Options: Choosing the Right Transformation
    Proceedings of the Twentieth International Conference on Machine Learning (ICML 2003)
    [ pdf ]

  • Ravindran, B. and Barto, A.G. (2003)
    SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi Markov Decision Processes
    Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI 03).
    [ pdf ]

  • Ravindran, B. and Barto, A. G. (2003)
    An Algebraic Approach to Abstraction in Reinforcement Learning
    Proceedings of the Twelfth Yale Workshop on Adaptive and Learning Systems, pages 109-114, Yale University.
    [ pdf ]

  • Barto, A. G. (2003)
    Reinforcement learning
    In Handbook of Brain Theory and Neural Networks, Second Edition M.A. Arbib (Ed.), pages 963-968. Cambridge: MIT Press..

  • Barto, A. G. (2003)
    Reinforcement learning in motor control
    In Handbook of Brain Theory and Neural Networks, Second Edition M.A. Arbib (Ed.), pages 968-972. Cambridge: MIT Press..


    2002

  • McGovern, Amy , Moss, Eliot, and Andrew G. Barto (2002)
    Building a Basic Block Instruction Scheduler using Reinforcement Learning and Rollouts
    Machine Learning, Special Issue on Reinforcement Learning. Volume 49, Numbers 2/3, Pages 141-160.
    [ ps (200K) | gzipped ps (60K) | pdf (160K)]

  • Fagg, A. H., Shah, A., and Barto, A. G. (2002)
    A Computational Model of Muscle Recruitment for Wrist Movements
    Journal of Neurophysiology vol. 88; pages 3348 - 3358
    [ ps | pdf | large print pdf ]

  • Pickett, M., and Barto, A. G (2002)
    PolicyBlocks: An Algortithm for Creating Useful Macro-Actions in Reinforcement Learning
    Proceedings of the Nineteenth International Conference of Machine Learning
    [ ps ]

  • Ravindran, B. and Barto, A. G. (2002)
    Model Minimization in Hierarchical Reinforcement Learning
    Proceedings of the Fifth Symposium on Abstraction, Reformulation and Approximation (SARA 2002), pages 196-211, LNCS, Springer Verlag.
    [ gzipped pdf ]

  • Shah, A., Fagg, A. H., and Barto, A. G. (2002)
    Cortical Involvement in the Recruitment of Wrist Muscles
    poster presented at Neural Control of Movement Conference, April 14-21, 2002, Naples, FL;
    half-sized (26"x24") poster: [ ps | pdf ]

  • Kositsky, M. and Barto, A.G. (2002)
    The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback
    Neurocomputing, 44-46, pages 889-895, 2002.
    [ pdf ]

  • Kositsky, M. and Barto, A.G. (2002)
    Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay
    Dietterich, T.G., Becker, S., and Ghahramani, Z. (eds.) Advances in Neural Information Processing Systems 14 (NIPS) 2002.
    [ pdf ]

  • Houk, J. C., Fagg, A. H., Barto, A. G. (2002)
    Fractional Power Damping Model of Joint Motion
    In Progress in Motor Control: Structure-Function Relations in Voluntary Movements,(M. Latash, Ed.), vol II, pages 147-178
    [ ps ]


    2001

  • Perkins, T.J., and Barto, A.G. (2001)
    Lyapunov-Constrained Action Sets for Reinforcement Learning
    Proceedings of the Eighteenth International Conference on Machine Learning, pages 409-416.
    [ ps ]

  • Perkins, T.J., and Barto, A.G. (2001)
    Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis
    Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pages 242-247.
    [ ps ]

  • Rosenstein, M.T. and Barto, A.G. (2001)
    Robot weightlifting by direct policy search
    Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, vol. 2, 839-844.
    [ gzipped ps | pdf ]

  • Rosenstein, M.T. and Barto, A.G. (2001)
    A robotic weightlifter that learns to exploit dynamics
    Studies in Perception and Action VI: Eleventh International Conference on Perception and Action , 25-28.

  • Rosenstein, M.T. and Barto, A.G. (2001)
    From elementary movements to coordination for a robotic weightlifter
    Abstracts of the Third International Symposium on Progress in Motor Control: From Basic Science to Applications, p. 40.

  • Ravindran, B. and Barto, A. G. (2001)
    Symmetries and Model Minimization of Markov Decision Processes
    Computer Science Technical Report 01-43, University of Massachusetts, Amherst, MA.
    [ gzipped ps ]

  • McGovern, Amy , and Andrew G. Barto (2001)
    Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density
    2001 International Conference on Machine Learning
    [ ps (252K) | gzipped ps (160K) ]

  • Kositsky, M. and Barto, A. G. (2001)
    Nonlinear Damping Dynamics and the Variability of Rapid Aimed Movements
    Technical Report 01-15, Department of Computer Science, University of Massachusetts, Amherst.
    [ gzipped ps | gzipped pdf ]

  • Kositsky, M. and Barto, A. G. (2001)
    Nonlinear Damping Dynamics and the Variability of Rapid Aimed Movements
    Poster presented at the 2001 Conference on Neural Control of Movement, Seville, Spain.
    one-page poster: [ gzipped ps | gzipped pdf ]

  • Kositsky, M. and Barto, A. G. (2001)
    The emergence of multiple movement through learning with noisy efferent signals and delayed sensory feedback
    Tenth Annual Computational Neuroscience Meeting, San Francisco and Pacific Grove, California, 2001.
    [ pdf ]

  • Kositsky, M. and Barto, A. G. (2001)
    Reinforcement learning model for noisy environment and delayed feedback: natural emergence of movement units
    Fifth International Conference on Cognitive and Neural Systems, Boston, Massachusetts, 2001.

  • Shah, A., Fagg, A. H., and Barto, A. G. (2001)
    A Computational Model of Muscle Recruitment for Wrist Movements,
    poster presented at Neural Control of Movement Conference, March 25-30, 2001, Seville, Spain
    half-sized (18"x31") poster: [ ps | pdf ]

  • Jonsson, A. and Barto, A. G. (2001)
    Automated State Abstraction for Options using the U-Tree Algorithm
    Advances in Neural Processing Information Systems 13, Cambridge, MA: MIT Press.
    [ gzipped ps ]


    2000

  • J. Randløv, A.G. Barto, and M.T. Rosenstein (2000)
    Combining reinforcement learning with a local control algorithm
    Proceedings of the Seventeenth International Conference on Machine Learning, 775-782.
    [ gzipped ps | pdf ]

  • R. Moll, T. Perkins, and A. Barto (2000)
    Machine Learning for Subproblem Selection
    Proceedings of the Seventeenth International Conference on Machine Learning (ICML-2000), P. Langley (Ed.),Morgan Kaufmann, San Francisco,CA, pages 615-622.
    [ ps ]


    1999

  • R. Moll, A. Barto, T. Perkins, and R. Sutton (1999)
    Learning Instance-Independent Value Functions to Enhance Local Search
    Advances in Neural Information Processing Systems 11 (NIPS11), M. S. Kearns, S. A. Solla, and D. A. Cohn (Eds.), Cambridge, MA: MIT Press, 1999, pages 1017-1023.
    [ ps ]

  • Schlesinger, M., and Barto, A. (1999)
    Optimal control methods for simulating the perception of causality in young infants
    Proceedings of the Twenty First Annual Conference of the Cognitive Science Society, pages 625-630. New Jersey: Lawrence Erlbaum.
    [ gzipped ps ]

  • McGovern, Amy, Moss, Eliot, and Barto, Andrew G. (1999)
    Basic-block Instruction Scheduling Using Reinforcement Learning and Rollouts
    Proceedings of the 1999 IJCAI workshop on learning and optimization.
    [ ps ]


    1998

  • Sutton, Richard S., and Barto, Andrew G. (1998)
    Reinforcement Learning: An Introduction
    MIT Press.
    [ Author Website | MIT Press Site for this book ]

  • Barto, A. G, Fagg, A. H., Sitkoff, N., and Houk, J. C. (1998)
    A Cerebellar Model of Timing and Prediction in the Control of Reaching
    Neural Computation, vol. 11, pages 565-594.
    [ ps | pdf ]

  • Crites, R. H., and Barto, A. G (1998)
    Elevator Group Control Using Multiple Reinforcement Learning Agents
    Machine Learning 33: 235-262.
    [ gzipped ps ]

  • Fagg, A. H., Zelevinsky, L., Barto, A. G., and Houk, J. C. (1998)
    A Pulse-Step Model of Control for Arm Reaching Movements
    Proceedings of the Spring Meeting on the Neural Control of Movement.

  • Fagg, A. H., Barto, A. G., and Houk, J. C.(1998)
    Learning to Reach Via Corrective Movements
    Proceedings of the Tenth Yale Workshop on Adaptive and Learning Systems, New Haven, CT.
    [ ps | html ]


    1997

  • R. E. Kettner, S. Mahamud, H. -C. Leung, N. Sitkoff, Houk, J. C., B. W. Peterson, and Barto, A. G. (1997)
    Prediction of Complex Two-Dimensional Trajectories by the Eye and by a Cerebellar Model of Smooth Eye Movements
    Journal of Neurophysiology, vol. 77; pages 2115-2130, 1997.
    [ ps | pdf ]

  • Fagg, A. H., Sitkoff, N., Barto, A. G., and Houk, J. C. (1997)
    Cerebellar Learning for Control of a Two-Link Arm in Muscle Space
    Proceedings of the IEEE Conference on Robotics and Automation, May, pages 2638-2644.
    [ gzipped ps ]

  • Fagg, A. H., Zelevinsky, L., Barto, A. G., and Houk, J. C. (1997)
    Using Crude Movements to Learn Accurate Motor Programs for Reaching
    Presented at the NIPS workshop: Can Artificial Cerebellar Models Compete to Control Robots? Dec. 5, Breckenridge, CO.
    [ ps ]

  • Fagg, A. H., Sitkoff, N., Barto, A. G., and Houk, J. C. (1997)
    A Computational Model of Cerebellar Learning for Limb Control
    Proceedings of the Spring 1997 Meeting of the Neural Control of Movement.
    [ gzipped ps poster text ]

  • Fagg, A. H., Sitkoff, N., Barto, A. G., and Houk, J. C. (1997)
    A Model of Cerebellar Learning for Control of Arm Movements Using Muscle Synergies
    Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, July 10-11, pages 6-12.
    [ gzipped ps ]

  • A. H. Fagg, N. Sitkoff, A. G. Barto, and Houk, J. C. (1997)
    Cerebellar Learning for Control of a Two-Link Arm in Muscle Space
    Proceedings of the IEEE Conference on Robotics and Automation (ICRA), May, pages 2638-2644.
    [ gzipped ps ]


    1996

  • S. J. Bradtke and A. G. Barto (1996)
    Linear Least-Squares Algorithms for Temporal Difference Learning
    Machine Learning, vol. 22, pages 33-57.

  • Houk, J.C., Buckingham, J.T., and Barto, A.G. (1996)
    Models of the Cerebellum and Motor Learning
    Behavioral and Brain Sciences vol. 19, pages 368-383.
    [
    pdf | ps ] (NOTE: These are pdf/ps copies of an unofficial online version that does not include figures. They were provided to give you an idea of the paper, but please go through the journal for the official version. Thanks.)


    1995

  • A. G. Barto, J. T. Buckingham, and Houk, J. C. (1995)
    A Predictive Switiching Model of Cerebellar Movement Control
    Neural Information Processing Systems 8, MIT Press, 1995, pages 138-144.
    [ gzipped ps ]

  • R. H. Crites, and A. G. Barto (1995)
    Improving Elevator Performance Using Reinforcement Learning
    Neural Information Processing Systems 8, MIT Press, 1995, pages 1017-1023.
    [ zipped ps ]

  • Houk, J. C., J. L. Adams, and Barto, A. G. (1995)
    A model of how the basal ganglia generates and uses neural signals that predict reinforcement
    In Models of Information Processing in the Basal Ganglia, J. C. Houk, J. Davis, and D. Beiser (Eds.), Cambridge, MA: MIT Press, 1995, pages 249-270.

  • A. G. Barto (1995)
    Adaptive critics and the basal ganglia
    In Models of Information Processing in the Basal Ganglia, J. C. Houk, J. Davis, and D. Beiser (Eds.), Cambridge, MA: MIT Press, 1995, pages 215-232.
    [ ps | pdf ] (note: this version is missing one figure)

  • J. T. Buckingham, Barto, A. G., and Houk, J. C. (1995)
    Adaptive Predictive Control with a Cerebellar Model
    Proceedings of the 1995 World Congress on Neural Networks, Volume 1, Lawrence Erlbaum Associates, Inc: Mahwah, NJ, 1995, pages 373-380

  • Barto, A. G. (1995)
    Reinforcement learning and dynamic programming
    Presented at IFAC'95, Conference on Man-Machine Systems, Cambridge, MA, June 1995.

  • A. G. Barto, S. J. Bradtke, and S. P. Singh (1995)
    Learning to act using real-time dynamic programming
    Artificial Intelligence, Special Volume on Computational Research on Interaction and Agency,
    72(1): 81-138, 1995.
    [ gzipped ps ]
    • Reprinted in Computational Theories of Interaction and Agency, P. E. Agre & S. J. Rosenschein (Eds.), Cambridge, MA: MIT Press, 1996.
    • Also appeared as CMPSCI Technical Report 93-02, University of Massachusetts, January 1993. (Supercedes TR 91-57.)

  • Crites RH, and Barto, A. G. (1995)
    An Actor/Critic Algorithm that is Equivalent to Q-Learning
    NIPS 7.
    [ zipped ps ]


    1994

  • J. T. Buckingham, J. C. Houk, and A. G. Barto (1994)
    Controlling a nonlinear spring-mass system with a cerebellar model
    8th Yale Workshop on Adaptive and Learning Systems, Yale University, June 1994, pages 1-6.

  • S. J. Bradtke, A. G. Barto, and B. E. Ydstie (1994)
    A reinforcement learning method for direct adaptive linear quadratic control
    8th Yale Workshop on Adaptive and Learning Systems, Yale University, June 1994, pages 85-96.

  • V. Gullapalli and A. Barto (1994)
    Convergence of indirect adaptive asynchronous value iteration algorithms
    Advances in Neural Information Processing Systems 6, J.D. Cowan, G. Tesauro and J. Alspector (Eds.), San Francisco: Morgan Kauffmann, 1994, pages 695-702.

  • A. Barto and M. Duff (1994)
    Monte Carlo matrix inversion and reinforcement learning
    Advances in Neural Information Processing Systems 6, J.D. Cowan, G. Tesauro and J. Alspector (Eds.), San Francisco: Morgan Kauffmann, 1994, pages 687-694.

  • S. P. Singh, A. G. Barto, R. Grupen, and C. Connolly (1994)
    Robust reinforcement learning in motion planning
    Advances in Neural Information Processing Systems 6, J.D. Cowan, G. Tesauro and J. Alspector (Eds.), San Francisco: Morgan Kauffmann, 1994, pages 655-662.

  • V. Gullapalli, A. G. Barto, and R. A. Grupen (1994)
    Learning admittance mappings for force-guided assembly
    Proceedings of the 1994 International Conference on Robotics and Automation, 1994, pages 2633-2638.

  • S. J. Bradtke and A. G. Barto (1994)
    New Algorithms for Temporal Difference Learning
    Machine Learning, 108, Special Issue on Reinforcement Learning.

  • Barto, A. G. (1994)
    Reinforcement Learning Control
    Current Opinion in Neurobiology, 4:888-893, 1994.

  • Barto, A. G. (1994)
    Learning as hillclimbing in weight space
    In Handbook of Brain Theory and Neural Networks, M.A. Arbib (Ed.), Cambridge: MIT Press..

  • Barto, A. G. (1994)
    Reinforcement learning in motor control
    In Handbook of Brain Theory and Neural Networks, M.A. Arbib (Ed.), Cambridge: MIT Press..

  • Barto, A. G.(1994)
    Reinforcement Learning
    In Handbook of Brain Theory and Neural Networks, M.A. Arbib (Ed.), Cambridge: MIT Press..

  • S. J. Bradtke, B. E. Ydstie, and A. G. Barto (1994)
    Adaptive linear quadratic control using policy iteration
    CMPSCI Technical Report 94-49, University of Massachusetts, June 1994. Submitted to IEEE Transactions on Automatic Control, April 1994.


    before 1994




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