A. G. Barto's Publications

Following is a list of A.G. Barto's publications in reverse chronological order. Click here for a comprehensive listing of all publications of the Autonomous Learning Laboratory.

To jump to a specific year:
| 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1996 | 1995 | 1994 | 1993 | 1992 | 1991 | 1990 | 1989 | 1987 | 1986 | 1985 | 1983 | 1982 | 1981 | 1978 | 1976 | 1975 |



    2015

  • Niekum, S., Osentoski, S., Atkeson, C.G., and Barto, A.G. (2015)
    Online Bayesian changepoint detection for articulated motion models
    IEEE International Conference on Robotics and Automation
    [pdf]

  • Niekum, S., Osentoski, S., Atkeson, Konidaris, G.D., Chitta, S., Marthi, B., and Barto, A.G. (2014)
    Learning grounded finite-state representations from unstructured demonstrations
    International Journal of Robotics Research, vol. 34(2), pp. 131-157
    [abstract] [freely accessible draft] [video]


    2014

  • Niekum, S., Osentoski, S., Atkeson, C.G., and Barto, A.G. (2014)
    Learning articulation changepoint models from demonstration
    RSS Workshop on Learning Plans with Context from Human Signals
    [pdf]

  • Niekum, S., Osentoski, S., Atkeson, C.G., and Barto, A.G. (2014)
    CHAMP: Changepoint detection using approximate model parameters
    Technical report CMU-RI-TR-14-10, Robotics Institute, Carnegie Mellon University
    [pdf]

  • da Silva, B.C., Konidaris, G., and Barto, A.G. (2014)
    Active learning of parameterized skills
    Proceedings of the 31st International Conference on Machine Learning (ICML 2014)
    [pdf]

  • da Silva, B.C., Baldassarre, G., Konidaris, G., and Barto, A.G. (2014)
    Learning parameterized motor skills on a humanoid robot
    Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA 2014)
    [pdf] [video]


    2013

  • Barto, A., Mirolli, M., and Baldasarre, G. (2013)
    Novelty or surprise?
    Frontiers in Cognitive Science, 11, doi: 10.3389/fpsyg.2013.00907
    [Frontiers link]

  • Barto, A.G., Konidaris, G.D., and Vigorito, C. M. (2013)
    Behavioral hierarchy: exploration and representation
    G. Baldassarre and M. Mirolli, editors, Computatonal and Robotic Models of the Hierarchical Organization of Behavior, pp. 13-46, Springer
    [feely accessible draft]

  • Levy, Y.Z., Barto, A.G., and Meyer J.S. (2013)
    A computational hypothesis for allostasis: delineation of substance dependence, conventional therapies, and alternative treatments
    Frontiers in Psychiatry 4:167. doi: 10.3389/fpsyt.2013.00167
    [Frontiers link]

  • Shah, A., Fagg, A., and Barto, A. (2013)
    A dual process account of coarticulation in motor skill acquisition
    Journal of Motor Behavior, vol. 45, pp. 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
    [ pdf ] [ video ]

  • Barto, A. (2013)
    Intrinsic motivation and reinforcement learning
    In G. Baldassarre and M. Mirolli (Eds.), Intrinsically Motivated Learning in Natural and Artificial Systems, pp. 17-47 Springer
    [ abstract ]

  • Kuindersma, S.R., Grupen, R.A., and Barto, A.G. (2013)
    Variable risk control via stochastic optimization
    International Journal of Robotics Research, vol. 32, pp. 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, pp. 71-76
    [ pdf ]


    2012

  • Dabney, W., and Barto A.G. (2012)
    Adaptive step-size for online temporal difference learning
    Twenty-Sixth Conference on Artificial Intelligence (AAAI 12)
    [ pdf ]

  • 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, pp. 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, pp. 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), pp. 1-8
    [ pdf ]

  • da Silva, B.C., and Barto, A.G. (2012)
    TD-Δπ: a model-free algorithm for efficient exploration
    Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012)
    [ pdf ]

  • da Silva, B.C., Barto, A.G., and Kurose, J. (2012)
    Designing adaptive sensing policies for meteorological phenomena via spectral analysis of radar images
    Technical Report UM-CS-2012-006, Department of Computer Science, University of Massachusetts Amherst USA
    [ pdf ]

  • da Silva, B.C., Konidaris, G.D., and Barto, A.G. (2012)
    Learning parameterized skills
    Proceedings of the Twenty Ninth International Conference on Machine Learning, pp. 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, pp. 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, pp. 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, pp. 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), pp. 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), pp. 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, pp. 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 (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, vol. 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), pp. 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), vol. 2, no. 2, pp. 83-90
    [ pdf ]

  • Singh, S., Lewis, R.L., Barto, A.G., and Sorg, J. (2010)
    Intrinsically motivated reinforcement learning: an evolutionary perspective
    IEEE Transactions on Autonomous Mental Development (IEEE TAMD), vol. 2, no. 2, pp. 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), vol. 2, no. 2, pp. 132-143
    [
    pdf ]


    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), pp. 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, pp. 2601-2606. Austin, TX
    [ pdf ]

  • Konidaris, G.D., and Barto, A.G. (2009)
    Towards the autonomous acquisition of robot skill hierarchies (poster abstract)
    Robotics: Science and Systems Workshop on Bridging the Gap Between High-Level Discrete Representations and Low-Level Continuous Behaviors (RSS Workshop), Seattle, WA
    [ 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), 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), pp. 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), pp. 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), 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), 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, 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, 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
    [Also published as Miguel, I., and Tuml, W. (Eds.) Lecture Notes in Artificial Intelligence: Abstraction, Reformulation, and Approximation, vol. 4612, pp. 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), Toronto, Ontario, Canada. Abstract published in BMC Neuroscience 2007, 8 (Suppl 2): P203
    [ 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
    [ pdf ]

  • Barringer, C.W., and Barto, A.G. (2007)
    Discrete submovements using predictive models
    poster presented at Neural Control of Movement Conference, 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
    [ 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, pp. 2259-2301
    [ 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
    [ 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
    [ 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
    [ 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
    [ 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
    [ 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, 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
    [
    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
    [ 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
    [ 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
    [ 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
    [ ps ]

  • Şimşek, Ö., 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
    [ 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, pp. 329-346

  • Barto, A.G., and Şimşek, Ö. (2005)
    Intrinsic motivation for reinforcement learning systems
    Proceedings of the Thirteenth Yale Workshop on Adaptive and Learning Systems, pp. 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
    [ 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
    [ ps | pdf | bibtex ] NOTE: an improved version appeared as a technical report: [ pdf | ps ]

  • Si. J., Barto, A. G., Powell, W. B., Wunch D. (Eds.) (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. (Eds.), Handbook of Learning and Approximate Dynamic Programming, Chapter 2, pages 47-64 Wiley-IEEE Press, Piscataway, NJ
    [ pdf ]

  • 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. (Eds.) Handbook of Learning and Approximate Dynamic Programming, Chapter 14, pages 359-380 Wiley-IEEE Press, Piscataway, NJ
    [ pdf ]

  • 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, pp. 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), pp. 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. 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, pp. 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.), pp. 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.), pp. 968-972. Cambridge: MIT Press


    2002

  • McGovern, A., Moss, E., and Barto, A.G. (2002)
    Building a basic block instruction scheduler using reinforcement learning and rollouts
    Machine Learning, Special Issue on Reinforcement Learning, vol. 49, no. 2/3, pp. 141-160
    [ pdf ]

  • Fagg, A.H., Shah, A., and Barto, A.G. (2002)
    A computational model of muscle recruitment for wrist movements
    Journal of Neurophysiology, vol. 88, pp. 3348-3358
    [ pdf ]

  • Pickett, M., and Barto, A.G (2002)
    PolicyBlocks: an algorithm 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), pp. 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, Naples, FL
    : [ abstract ] [ half-sized (26"x24") poster 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, pp. 889-895
    [ 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)
    [ pdf ]

  • Houk, J.C., Fagg, A.H., Barto, A.G. (2002)
    Fractional power damping model of joint motion
    In M. Latash (Ed.) Progress in Motor Control: Structure-Function Relations in Voluntary Movements, vol II, pp. 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, pp. 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, pp. 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, pp. 839-844
    [ abstract ] [ 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, pp. 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, A., and Barto, A.G. (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 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
    [ 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
    [ 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, 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

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

  • R. Moll, Perkins, T., and Barto, A. (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, pp. 615-622
    [ ps ]


    1999

  • Moll, R., Barto, A., Perkins, T., and Sutton, R. (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, pp. 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, pp. 625-630. New Jersey: Lawrence Erlbaum.
    [ gzipped ps ]

  • McGovern, A., Moss, E., and Barto, A.G. (1999)
    Basic-block instruction scheduling using reinforcement learning and rollouts
    Proceedings of the 1999 IJCAI workshop on learning and optimization.
    [ ps ]


    1998

  • Sutton, R.S., and Barto, A.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.
    [ pdf ]

  • 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
    [ abstract ]

  • 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 ]


    1997

  • Kettner, R.E., Mahamud, S., Leung, H.-C., Sitkoff, N., Houk, J.C., Peterson, B.W., 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, pp. 2115-2130
    [ 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, pp. 2638-2644
    [ gzipped ps ]

  • Fagg, A.H., Zelevinsky, L., Barto, A.G., and Houk, J.C. (1997)
    Using crude corrective movements to learn accurate motor programs for reaching
    Presented at the NIPS workshop: Can Artificial Cerebellar Models Compete to Control Robots? 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, pp. 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), pp. 2638-2644
    [ gzipped ps ]

  • Moll, R., Barto, A.G., Perkins, T., and Sutton, R.S. (1997)
    Reinforcement learning and local search: a case study
    University of Massachusetts CMPSCI Tech. Report 9744
    [ pdf ]


    1996

  • Crites, R.H., and Barto, A.G. (1996)
    Improving elevator performance using reinforcement learning
    Advances in neural information processing systems 8: 1017-1023
    [ pdf ]

  • Bradtke, S.J., and Barto, A.G. (1996)
    Linear least-squares algorithms for temporal difference learning
    Machine Learning, vol. 22, pp. 33-57
    [ pdf]

  • Houk, J.C., Buckingham, J.T., and Barto, A.G. (1996)
    Models of the cerebellum and motor learning
    Behavioral and Brain Sciences vol. 19, pp. 368-383
    [
    pdf ]


    1995

  • Barto, A.G., Buckingham, J.T., and Houk, J.C. (1995)
    A predictive switching model of cerebellar movement control
    Neural Information Processing Systems 8, MIT Press, pp. 138-144
    [ gzipped ps ]

  • Houk, J.C., Adams, J.L., 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, pp. 249-270
    [ pdf ]

  • 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, pp. 215-232
    [ pdf ] (note: this version is missing one figure)

  • Buckingham, J.T., 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, pp. 373-380

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

  • Barto, A.G., Bradtke, S.J., and Singh, S.P. (1995)
    Learning to act using real-time dynamic programming
    Artificial Intelligence, Special Volume on Computational Research on Interaction and Agency, 72(1): 81-138
    [ pdf ]
    • 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, R.H. and Barto, A.G. (1995)
    An actor/critic algorithm that is equivalent to Q-learning
    Advances in Neural Information Processing Systems 7: 401-408
    [ pdf ]


    1994

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

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

  • Gullapalli, V., and Barto, A. (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, pp. 695-702
    [ pdf

  • Barto, A., and Duff, M. (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, pages 687-694.
    [ pdf ]

  • Singh, S.P., Barto, A.G., Grupen, R., and Connolly, C. (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, pp. 655-662
    [ pdf ]

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

  • Bradtke, S.J., and Barto, A.G. (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
    [ abstract ]

  • 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

  • Bradtke, S.J., Ydstie, B.E., and Barto, A.G. (1994)
    Adaptive linear quadratic control using policy iteration
    American Control Conference, vol. 3, pp. 3475-3479. IEEE.
    CMPSCI Technical Report 94-49, University of Massachusetts
    [ pdf ]


    1993

  • Houk, J.C., Kiefer, J., and Barto, A.G. (1993)
    Distributed motor commands in the limb premotor network
    Trends in Neuroscience 16(1): 27-33
    [pdf ]

  • Berthier, N.E., Singh, S.P., Barto, A.G., and Houk, J.C. (1993)
    Distributed representation of limb motor programs in arrays of adjustable pattern generators
    Journal of Cognitive Neuroscience, 5(1): 56-78
    [ abstract ]

  • Barto, A.G., and Gullapalli, V. (1993)
    Neural networks and adaptive control
    In P. Rudomin, M. A. Arbib, F. Cervantes-Perez, and R. Romo (Eds.), Neuroscience: From Neural Networks to Artificial Intelligence, Research Notes in Neural Computation, vol. 4, Springer-Verlag, pp. 471-493
    [ abstract ]


    1992

  • Gullapalli, V., Grupen, R., and Barto, A.G. (1992)
    Learning reactive admittance control
    Proceedings of the 1992 IEEE International Conference on Robotics and Automation, IEEE
    [ pdf ]

  • Gullapalli, V., and Barto, A.G. (1992)
    Shaping as a method for accelerating reinforcement learning
    In Proceedings of the 1992 IEEE International Symposium on intelligent Control, pp. 554-559. IEEE
    [ abstract ]

  • Barto, A.G., and Bradtke, S.J. (1992)
    Learning to solve stochastic optimal path problems using real-time dynamic programming
    Proceedings of the Seventh Yale Workshop on Adaptive and Learning Systems, New Haven, CT, pp. 143-148

  • Barto, A.G. (1992)
    Reinforcement learning and adaptive critic methods
    In D.A. White and D.A. Sofge, editors, Handbook of Intelligent Control, New York: Van Nostrand Reinhold, pp. 469-491

  • Sutton, R.S., Barto, A.G., and Williams, R.J. (1992)
    Reinforcement learning is direct adaptive optimal control Control Systems, IEEE 12.2: 19-22
    [ pdf ]

  • Houk, J.C., and Barto, A.G. (1992)
    Distributed sensorimotor learning
    In G. E. Stelmach and J. Requin, (Eds.) Tutorials in Motor Behavior II, Elsevier Science Publishers B.V.: Amsterdam, pp. 71-100
    [Also appeared as NPB Technical Report #1, Center for Neuroscience Research on Neuronal Populations and Behavior, Northwestern University, Dec. 1991]


    1991

  • Jacobs, R.A., Jordan, M.I., and Barto, A.G. (1991)
    Task decomposition through competition in a modular connectionist architecture: the what and where vision tasks
    Cognitive Science, 15: 219-250
    [ pdf ]

  • Barto, A.G. (1991)
    Some learning tasks from a control perspective
    In L. Nadel and D. Stein, editors, Lectures in Complex Systems, Addison-Wesley, pp. 195-223
    [Also appeared as COINS Technical Report 90-122, University of Massachusetts at Amherst, December 1990]
    [ pdf ]


    1990

  • Yee, R.C., Saxena, S., Utgoff, P.E., and Barto, A.G. (1990)
    Explaining temporal differences to create useful concepts for evaluating states
    In Proceedings of the 8th National Conference on Artificial Intelligence, pp. 882-888. AAAI Press/MIT Press
    [ pdf ]

  • Sutton, R. S. and Barto, A.G. (1990)
    Time-derivative models of Pavlovian reinforcement
    In M. Gabriel and J. Moore (Eds.), Learning and Computational Neuroscience: Foundations of Adaptive Networks, The MIT Press: Cambridge, MA, pp. 497-537
    [ abstract ][freely available draft ]

  • Barto, A.G., Sutton, R.S., and Watkins, C.J.C.H. (1990)
    Learning and sequential decision making
    In M. Gabriel and J.W. Moore (Eds.), Learning and Computational Neuroscience: Foundations of Adaptive Networks, MIT Press: Cambridge, MA, pp. 539-602
    [ pdf ] [ abstract ]

  • Barto, A.G., Sutton, R.S., and Watkins, C.J.C.H. (1990)
    Sequential decision problems and neural networks
    Advances in neural information processing systems, pp. 686-693
    [ pdf ]

  • Barto, A.G. (1990)
    Connectionist learning for control
    In W. T. Miller, R. S. Sutton and P. J. Werbos (Eds.), Neural Networks for Control, pp. 5-58. Cambridge, MA: The MIT Press
    [ pdf ]

  • Barto, A.G. and Singh, S.P. (1990)
    Reinforcement learning and dynamic programming
    Proceedings of the Sixth Yale Workshop on Adaptive and Learning Systems, New Haven, CT. pp. 83-88

  • Barto, A.G. and Singh, S.P. (1990)
    On the computational economics of reinforcement learning
    In D.S. Touretzky, J.L. Elman, T.J. Sejnowski and G.E. Hinton (Eds.), Proceedings of the 1990 Connectionist Models Summer School, San Mateo, CA: Morgan Kaufmann, pp. 35-44
    [ pdf ]


    1989

  • Barto, A.G. (1989)
    From chemotaxis to cooperativity: Abstract exercises in neuronal learning strategies
    In R. Durbin, C. Miall and G. Mitchison (Eds.), The Computing Neuron, pp. 73-98. Wokingham, England: Addison-Wesley
    [ pdf ]

  • Barto, A.G., Sutton, R.S., and Watkins, C.J.C.H. (1989)
    Learning and sequential decision making
    In Learning and computational neuroscience
    [ pdf ]


    1987

  • Barto, A.G. (1987)
    An approach to learning control surfaces by connectionist systems
    In M.A. Arbib and A.R. Hanson (Eds.), Vision, Brain and Cooperative Computation, MIT Press/ Bradford Books, Cambridge, MA

  • Barto, A.G., and Jordan, M.I. (1987)
    Gradient following without back-propagation in layered networks
    Proceedings of the First IEEE Annual Conference on Neural Networks, San Diego, CA, pp. II-629-II-636
    [ pdf ]

  • Sutton, R.S., and Barto, A.G. (1987)
    A temporal-difference model of classical conditioning
    Proceedings of the ninth annual conference of the cognitive science society, pp. 355-378
    [ pdf ] [also TR87-509.2, Computer & Intelligent Systems Laboratory, GTE Laboratories Inc., Waltham, MA, 1987]


    1986

  • Barto, A.G. (1986)
    Game-theoretic cooperativity in networks of self-interested units
    In J. S. Denker (Ed.), Neural Networks for Computing, 151(1): 41-46. AIP Publishing. American Institute of Physics, NY
    [ abstract ]

  • Barto, A.G., Anandan, P., and Anderson, C.W. (1986)
    Cooperativity in networks of pattern recognizing stochastic learning automata
    In K. S. Narendra (Ed.), Adaptive and Learning Systems: Theory and Applications, Plenum, New York
    [ abstract ]

  • Moore, J.W., Desmond, J.E., Berthier, N.E., Blazis, E.J., Sutton, R.S., and Barto, A.G. (1986)
    Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element. Response topography, neuronal firing, and interstimulus intervals
    Behavioural Brain Research, 21: 143-154
    [ pdf ]


    1985

  • Barto, A.G. (1985)
    Adaptive neural networks for learning control: some computational experiments
    Proceedings of the IEEE Workshop on Intelligent Control, Rensselaer Polytechnic Institute, Troy, NY

  • Barto, A.G. (1985)
    Learning by statistical cooperation of self-interested neuron-like computing elements
    Human Neurobiology, 4: 229-256
    [ pdf ]

  • Barto, A.G., and Anandan, P. (1985)
    Pattern recognizing stochastic learning automata
    IEEE Transactions on Systems, Man, and Cybernetics, 15: 360-375
    [ abstract ]

  • Barto, A.G., and Anderson, C.W. (1985)
    Structural learning in connectionist systems
    Proceedings of the Seventh Annual Conference of the Cognitive Science Society, Irvine, CA

  • Selfridge, O., Sutton, R.S., and Barto, A.G. (1985)
    Training and tracking in robotics
    Proceedings of the Ninth International Joint Conference on Artificial Intelligence, pp. 670-672. San Mateo, CA: Morgan Kaufmann
    [ pdf ]

  • Moore, J., Desmond, J., Berthier, N., Blazis, D., Sutton, R.S., and Barto, A.G. (1985)
    Connectionist learning in real time: Sutton-Barto adaptive element and classical conditioning of the nictitating membrane response
    Seventh Annual Conference of the Cognitive Science Society, pp. 318-322
    [ pdf ]


    1983

  • Barto, A.G., and Sutton, R.S. (1983)
    Neural problem solving COINS Technical Report 83-03, University of Massachusetts
    [ pdf ]

  • Barto, A.G., Sutton, R.S., and Anderson, C.W. (1983)
    Neuronlike elements that can solve difficult learning control problems
    IEEE Transactions on Systems, Man, and Cybernetics, 13: 835-846
    [ abstract ] [ pdf ]

      Reprinted in J. A. Anderson and E. Rosenfeld (Eds.), Neurocomputing: Foundations of Research, pp. 535-549, MIT Press, Cambridge, MA, 1988




    1982

  • Barto, A.G., Anderson, C.W., and Sutton, R.S. (1982)
    Synthesis of nonlinear control surfaces by a layered associative search network
    Biological Cybernetics, 43: 175-185
    [ pdf ]

  • Barto, A.G., and Sutton, R. S. (1982)
    Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element
    Behavioural Brain Research, 4:221-235
    [ pdf ]

  • Barto, A.G., Sutton, R.S., and Anderson, C.W. (1982)
    Spatial learning simulation systems
    Proceedings of the 10th IMACS World Congress on Systems Simulation and Scientific Computation, pp. 204-206


    1981

  • Barto, A.G., and Sutton, R.S. (1981)
    Goal seeking components for adaptive intelligence: An initial assessment
    AFWAL-TR-81-1070, Publisher Air Force Wright Aeronautical Laboratories
    [ abstract and pdf link ]

  • Barto, A.G., and Sutton, R.S. (1981)
    Landmark learning: an illustration of associative search
    Biological Cybernetics, 42(1): 1-8
    [ pdf ]

  • Barto, A.G., Sutton, R.S., and Brouwer, P.S. (1981)
    Associative search network: a reinforcement learning associative memory
    Biological Cybernetics, 40(3): 201-211
    [ pdf ]

  • Sutton, R.S., and Barto, A.G. (1981)
    An adaptive network that constructs and uses an internal model of its environment
    Cognition and Brain Theory, 4(3): 217-246
    [ pdf ]

  • Sutton, R.S., and Barto, A.G. (1981)
    Toward a modern theory of adaptive networks: expectation and prediction
    Psychological Review, 88: 135-171
    [ pdf ]


    1978

  • Barto, A.G. (1978)
    Discrete and continuous models
    International Journal of General Systems, 4: 163-177.
    [ abstract ]

  • Barto, A.G. (1978)
    A note on pattern reproduction in tesselation structures
    Journal of Computer and Systems Sciences, 16: 445-455
    [ pdf ]

  • Barto, A.G. (1978)
    Structurally invariant linear models of structurally varying linear systems
    Applied General Systems Research NATO Conference Series Volume 5, Springer, pp. 435-451
    [ abstract ]


    1976

  • Barto, A.G. (1976)
    A neural network simulation method using the Fast Fourier Transform
    IEEE Transactions on Systems, Man, and Cybernetics, SMC-5: 863-867
    [ pdf ]


    1975

  • Barto, A.G. (1975)
    Cellular Automata as Models of Natural Systems
    Ph.D. dissertation, University of Michigan, Department of Computer and Communication Science
    [ pdf ]

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