Department of Computer Science, University of Massachusetts Amherst
List of publications from the DBLP Bibliography Server - FAQ
- CSB - MetaPress - Google - Bing - Yahoo
 | 2012 | |
|---|---|---|
| j20 |      | George Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Robot learning from demonstration by constructing skill trees. I. J. Robotic Res. 31(3): 360-375 (2012) |
| c62 | | William Dabney, Andrew G. Barto: Adaptive Step-Size for Online Temporal Difference Learning. AAAI 2012 |
| c61 | | Bruno C. da Silva, Andrew G. Barto: TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI 2012 |
| c60 | | |
| c59 | | |
| c58 | | Scott Niekum, Sarah Osentoski, George Konidaris, Andrew G. Barto: Learning and generalization of complex tasks from unstructured demonstrations. IROS 2012: 5239-5246 |
| c57 | | Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Variational Bayesian Optimization for Runtime Risk-Sensitive Control. Robotics: Science and Systems 2012 |
| 2011 | ||
| c56 | | George Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Autonomous Skill Acquisition on a Mobile Manipulator. AAAI 2011 |
| c55 | | Scott Niekum, Andrew G. Barto: Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Lifelong Learning 2011 |
| c54 | | Scott Niekum, Lee Spector, Andrew G. Barto: Evolution of reward functions for reinforcement learning. GECCO (Companion) 2011: 177-178 |
| c53 | | Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Learning dynamic arm motions for postural recovery. Humanoids 2011: 7-12 |
| c52 |  | |
| c51 | | Scott Niekum, Andrew G. Barto: Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. NIPS 2011: 1818-1826 |
| 2010 | ||
| j19 | | Satinder P. Singh, Richard L. Lewis, Andrew G. Barto, Jonathan Sorg: Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective. IEEE T. Autonomous Mental Development 2(2): 70-82 (2010) |
| j18 | | Scott Niekum, Andrew G. Barto, Lee Spector: Genetic Programming for Reward Function Search. IEEE T. Autonomous Mental Development 2(2): 83-90 (2010) |
| j17 | | Christopher M. Vigorito, Andrew G. Barto: Intrinsically Motivated Hierarchical Skill Learning in Structured Environments. IEEE T. Autonomous Mental Development 2(2): 132-143 (2010) |
| c50 | | George Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen: Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories. NIPS 2010: 1162-1170 |
| r1 | | Andrew G. Barto: Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning 2010: 19-22 |
| 2009 | ||
| c49 | | George Konidaris, Andrew G. Barto: Efficient Skill Learning using Abstraction Selection. IJCAI 2009: 1107-1112 |
| c48 | | George Konidaris, Andrew G. Barto: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining. NIPS 2009: 1015-1023 |
| 2008 | ||
| c47 | | Christopher M. Vigorito, Andrew G. Barto: Hierarchical Representations of Behavior for Efficient Creative Search. AAAI Spring Symposium: Creative Intelligent Systems 2008: 135-141 |
| c46 | | |
| 2007 | ||
| j16 | | |
| c45 | | Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf: Repairing Disengagement With Non-Invasive Interventions. AIED 2007: 195-202 |
| c44 | | George Konidaris, Andrew G. Barto: Building Portable Options: Skill Transfer in Reinforcement Learning. IJCAI 2007: 895-900 |
| c43 | | |
| c42 | | Anders Jonsson, Andrew G. Barto: Active Learning of Dynamic Bayesian Networks in Markov Decision Processes. SARA 2007: 273-284 |
| c41 | | Christopher M. Vigorito, Deepak Ganesan, Andrew G. Barto: Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks. SECON 2007: 21-30 |
| 2006 | ||
| j15 | | Anders Jonsson, Andrew G. Barto: Causal Graph Based Decomposition of Factored MDPs. Journal of Machine Learning Research 7: 2259-2301 (2006) |
| j14 | | Michael T. Rosenstein, Andrew G. Barto, Richard E. A. Van Emmerik: Learning at the level of synergies for a robot weightlifter. Robotics and Autonomous Systems 54(8): 706-717 (2006) |
| c40 | | Alicia P. Wolfe, Andrew G. Barto: Decision Tree Methods for Finding Reusable MDP Homomorphisms. AAAI 2006: 530-535 |
| c39 | | George Konidaris, Andrew G. Barto: Autonomous shaping: knowledge transfer in reinforcement learning. ICML 2006: 489-496 |
| c38 | | Özgür Simsek, Andrew G. Barto: An intrinsic reward mechanism for efficient exploration. ICML 2006: 833-840 |
| c37 | | Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto: Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. Intelligent Tutoring Systems 2006: 453-462 |
| c36 | | |
| 2005 | ||
| c35 | | Anders Jonsson, Andrew G. Barto: A causal approach to hierarchical decomposition of factored MDPs. ICML 2005: 401-408 |
| c34 | | Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto: Identifying useful subgoals in reinforcement learning by local graph partitioning. ICML 2005: 816-823 |
| c33 | | Özgür Simsek, Andrew G. Barto: Learning Skills in Reinforcement Learning Using Relative Novelty. SARA 2005: 367-374 |
| 2004 | ||
| c32 | | Özgür Simsek, Andrew G. Barto: Using relative novelty to identify useful temporal abstractions in reinforcement learning. ICML 2004 |
| c31 | | Satinder P. Singh, Andrew G. Barto, Nuttapong Chentanez: Intrinsically Motivated Reinforcement Learning. NIPS 2004 |
| 2003 | ||
| j13 | | Andrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(1-2): 41-77 (2003) |
| j12 | | Andrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(4): 341-379 (2003) |
| c30 | | Balaraman Ravindran, Andrew G. Barto: Relativized Options: Choosing the Right Transformation. ICML 2003: 608-615 |
| c29 | | Balaraman Ravindran, Andrew G. Barto: SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI 2003: 1011-1018 |
| 2002 | ||
| j11 | | Michael Kositsky, Andrew G. Barto: The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback. Neurocomputing 44-46: 889-895 (2002) |
| j10 | | Theodore J. Perkins, Andrew G. Barto: Lyapunov Design for Safe Reinforcement Learning. Journal of Machine Learning Research 3: 803-832 (2002) |
| j9 | | Amy McGovern, J. Eliot B. Moss, Andrew G. Barto: Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts. Machine Learning 49(2-3): 141-160 (2002) |
| c28 | | Marc Pickett, Andrew G. Barto: PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. ICML 2002: 506-513 |
| c27 | | Balaraman Ravindran, Andrew G. Barto: Model Minimization in Hierarchical Reinforcement Learning. SARA 2002: 196-211 |
| 2001 | ||
| c26 | | Amy McGovern, Andrew G. Barto: Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. ICML 2001: 361-368 |
| c25 | | Theodore J. Perkins, Andrew G. Barto: Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML 2001: 409-416 |
| c24 | | Theodore J. Perkins, Andrew G. Barto: Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. IJCAI 2001: 242-247 |
| c23 | | Michael T. Rosenstein, Andrew G. Barto: Robot Weightlifting By Direct Policy Search. IJCAI 2001: 839-846 |
| c22 | | Michael Kositsky, Andrew G. Barto: The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. NIPS 2001: 43-50 |
| 2000 | ||
| c21 | | Robert Moll, Theodore J. Perkins, Andrew G. Barto: Machine Learning for Subproblem Selection. ICML 2000: 615-622 |
| c20 | | Jette Randløv, Andrew G. Barto, Michael T. Rosenstein: Combining Reinforcement Learning with a Local Control Algorithm. ICML 2000: 775-782 |
| c19 | | Anders Jonsson, Andrew G. Barto: Automated State Abstraction for Options using the U-Tree Algorithm. NIPS 2000: 1054-1060 |
| 1999 | ||
| j8 | | Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk: A Cerebellar Model of Timing and Prediction in the Control of Reaching. Neural Computation 11(3): 565-594 (1999) |
| 1998 | ||
| j7 | | Robert H. Crites, Andrew G. Barto: Elevator Group Control Using Multiple Reinforcement Learning Agents. Machine Learning 33(2-3): 235-262 (1998) |
| j6 | | Richard S. Sutton, Andrew G. Barto: Reinforcement Learning: An Introduction. IEEE Transactions on Neural Networks 9(5): 1054-1054 (1998) |
| c18 | | Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton: Learning Instance-Independent Value Functions to Enhance Local Search. NIPS 1998: 1017-1023 |
| 1997 | ||
| c17 | | Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk: Cerebellar learning for control of a two-link arm in muscle space. ICRA 1997: 2638-2644 |
| c16 | | Jeffrey F. Monaco, David G. Ward, Andrew G. Barto: Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments. NIPS 1997 |
| 1996 | ||
| j5 | | Steven J. Bradtke, Andrew G. Barto: Linear Least-Squares Algorithms for Temporal Difference Learning. Machine Learning 22(1-3): 33-57 (1996) |
| c15 | | Ron Papka, James P. Callan, Andrew G. Barto: Text-Based Information Retrieval Using Exponentiated Gradient Descent. NIPS 1996: 3-9 |
| c14 | | Michael O. Duff, Andrew G. Barto: Local Bandit Approximation for Optimal Learning Problems. NIPS 1996: 1019-1025 |
| c13 | | Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein: Reinforcement Learning for Mixed Open-loop and Closed-loop Control. NIPS 1996: 1026-1032 |
| 1995 | ||
| j4 | | Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh: Learning to Act Using Real-Time Dynamic Programming. Artif. Intell. 72(1-2): 81-138 (1995) |
| c12 | | Andrew G. Barto, James C. Houk: A Predictive Switching Model of Cerebellar Movement Control. NIPS 1995: 138-144 |
| c11 | | Robert H. Crites, Andrew G. Barto: Improving Elevator Performance Using Reinforcement Learning. NIPS 1995: 1017-1023 |
| 1994 | ||
| c10 | | Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen: Learning Admittance Mappings for Force-Guided Assembly. ICRA 1994: 2633-2638 |
| c9 | | Robert H. Crites, Andrew G. Barto: An Actor/Critic Algorithm that is Equivalent to Q-Learning. NIPS 1994: 401-408 |
| 1993 | ||
| c8 | | Satinder P. Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly: Robust Reinforcement Learning in Motion Planning. NIPS 1993: 655-662 |
| c7 | | Andrew G. Barto, Michael O. Duff: Monte Carlo Matrix Inversion and Reinforcement Learning. NIPS 1993: 687-694 |
| c6 | | Vijaykumar Gullapalli, Andrew G. Barto: Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms. NIPS 1993: 695-702 |
| c5 | | Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto: Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Machine Learning: From Theory to Applications 1993: 175-202 |
| 1991 | ||
| j3 | | N. E. Berthier, Andrew G. Barto, J. W. Moore: Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits. Biological Cybernetics 65(2): 99-105 (1991) |
| j2 | | Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto: Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Cognitive Science 15(2): 219-250 (1991) |
| c4 | | N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk: A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm. NIPS 1991: 611-618 |
| 1990 | ||
| c3 | | Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew G. Barto: Explaining Temporal Differences to Create Useful Concepts for Evaluating States. AAAI 1990: 882-888 |
| 1989 | ||
| c2 | | Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins: Sequential Decision Probelms and Neural Networks. NIPS 1989: 686-693 |
| 1985 | ||
| c1 | | Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto: Training and Tracking in Robotics. IJCAI 1985: 670-672 |
| 1978 | ||
| j1 | | Andrew G. Barto: A Note on Pattern Reproduction in Tessellation Structures. J. Comput. Syst. Sci. 16(3): 445-455 (1978) |
Colors in the list of coauthors
Last update Sun May 19 20:50:57 2013 CET by the DBLP Team —
Data released under the ODC-BY 1.0 license — See also our legal information page