Andrew G. Barto

Department of Computer Science, University of Massachusetts Amherst

	2011
75		George Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Autonomous Skill Acquisition on a Mobile Manipulator. AAAI 2011
74		Scott Niekum, Lee Spector, Andrew G. Barto: Evolution of reward functions for reinforcement learning. GECCO (Companion) 2011: 177-178
73		Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto: Learning dynamic arm motions for postural recovery. Humanoids 2011: 7-12
72		Philip Thomas, Andrew G. Barto: Conjugate Markov Decision Processes. ICML 2011: 137-144
71		Scott Niekum, Andrew G. Barto: Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Lifelong Learning 2011
70		Scott Niekum, Andrew G. Barto: Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. NIPS 2011: 1818-1826
	2010
69		George Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen: Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories. NIPS 2010: 1162-1170
68		Andrew G. Barto: Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning 2010: 19-22
67		Christopher M. Vigorito, Andrew G. Barto: Intrinsically Motivated Hierarchical Skill Learning in Structured Environments. IEEE T. Autonomous Mental Development 2(2): 132-143 (2010)
66		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)
65		Scott Niekum, Andrew G. Barto, Lee Spector: Genetic Programming for Reward Function Search. IEEE T. Autonomous Mental Development 2(2): 83-90 (2010)
	2009
64		George Konidaris, Andrew G. Barto: Efficient Skill Learning using Abstraction Selection. IJCAI 2009: 1107-1112
63		George Konidaris, Andrew G. Barto: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining. NIPS 2009: 1015-1023
	2008
62		Christopher M. Vigorito, Andrew G. Barto: Hierarchical Representations of Behavior for Efficient Creative Search. AAAI Spring Symposium: Creative Intelligent Systems 2008: 135-141
61		Özgür Simsek, Andrew G. Barto: Skill Characterization Based on Betweenness. NIPS 2008: 1497-1504
	2007
60		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
59		Balaraman Ravindran, Andrew G. Barto, Vimal Mathew: Deictic Option Schemas. IJCAI 2007: 1023-1028
58		George Konidaris, Andrew G. Barto: Building Portable Options: Skill Transfer in Reinforcement Learning. IJCAI 2007: 895-900
57		Anders Jonsson, Andrew G. Barto: Active Learning of Dynamic Bayesian Networks in Markov Decision Processes. SARA 2007: 273-284
56		Christopher M. Vigorito, Deepak Ganesan, Andrew G. Barto: Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks. SECON 2007: 21-30
55		Andrew G. Barto: Temporal difference learning. Scholarpedia 2(11): 1604 (2007)
	2006
54		Alicia P. Wolfe, Andrew G. Barto: Decision Tree Methods for Finding Reusable MDP Homomorphisms. AAAI 2006: 530-535
53		George Konidaris, Andrew G. Barto: Autonomous shaping: knowledge transfer in reinforcement learning. ICML 2006: 489-496
52		Özgür Simsek, Andrew G. Barto: An intrinsic reward mechanism for efficient exploration. ICML 2006: 833-840
51		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
50		George Konidaris, Andrew G. Barto: An Adaptive Robot Motivational System. SAB 2006: 346-356
49		Anders Jonsson, Andrew G. Barto: Causal Graph Based Decomposition of Factored MDPs. Journal of Machine Learning Research 7: 2259-2301 (2006)
48		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)
	2005
47		Anders Jonsson, Andrew G. Barto: A causal approach to hierarchical decomposition of factored MDPs. ICML 2005: 401-408
46		Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto: Identifying useful subgoals in reinforcement learning by local graph partitioning. ICML 2005: 816-823
45		Özgür Simsek, Andrew G. Barto: Learning Skills in Reinforcement Learning Using Relative Novelty. SARA 2005: 367-374
	2004
44		Özgür Simsek, Andrew G. Barto: Using relative novelty to identify useful temporal abstractions in reinforcement learning. ICML 2004
43		Satinder P. Singh, Andrew G. Barto, Nuttapong Chentanez: Intrinsically Motivated Reinforcement Learning. NIPS 2004
	2003
42		Balaraman Ravindran, Andrew G. Barto: Relativized Options: Choosing the Right Transformation. ICML 2003: 608-615
41		Balaraman Ravindran, Andrew G. Barto: SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI 2003: 1011-1018
40		Andrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(1-2): 41-77 (2003)
39		Andrew G. Barto, Sridhar Mahadevan: Recent Advances in Hierarchical Reinforcement Learning. Discrete Event Dynamic Systems 13(4): 341-379 (2003)
	2002
38		Marc Pickett, Andrew G. Barto: PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. ICML 2002: 506-513
37		Balaraman Ravindran, Andrew G. Barto: Model Minimization in Hierarchical Reinforcement Learning. SARA 2002: 196-211
36		Theodore J. Perkins, Andrew G. Barto: Lyapunov Design for Safe Reinforcement Learning. Journal of Machine Learning Research 3: 803-832 (2002)
35		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)
34		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)
	2001
33		Amy McGovern, Andrew G. Barto: Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. ICML 2001: 361-368
32		Theodore J. Perkins, Andrew G. Barto: Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML 2001: 409-416
31		Theodore J. Perkins, Andrew G. Barto: Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. IJCAI 2001: 242-247
30		Michael T. Rosenstein, Andrew G. Barto: Robot Weightlifting By Direct Policy Search. IJCAI 2001: 839-846
29		Michael Kositsky, Andrew G. Barto: The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. NIPS 2001: 43-50
	2000
28		Robert Moll, Theodore J. Perkins, Andrew G. Barto: Machine Learning for Subproblem Selection. ICML 2000: 615-622
27		Jette Randløv, Andrew G. Barto, Michael T. Rosenstein: Combining Reinforcement Learning with a Local Control Algorithm. ICML 2000: 775-782
26		Anders Jonsson, Andrew G. Barto: Automated State Abstraction for Options using the U-Tree Algorithm. NIPS 2000: 1054-1060
	1999
25		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
24		Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton: Learning Instance-Independent Value Functions to Enhance Local Search. NIPS 1998: 1017-1023
23		Richard S. Sutton, Andrew G. Barto: Reinforcement Learning: An Introduction. IEEE Transactions on Neural Networks 9(5): 1054-1054 (1998)
22		Robert H. Crites, Andrew G. Barto: Elevator Group Control Using Multiple Reinforcement Learning Agents. Machine Learning 33(2-3): 235-262 (1998)
	1997
21		Jeffrey F. Monaco, David G. Ward, Andrew G. Barto: Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments. NIPS 1997
	1996
20		Michael O. Duff, Andrew G. Barto: Local Bandit Approximation for Optimal Learning Problems. NIPS 1996: 1019-1025
19		Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein: Reinforcement Learning for Mixed Open-loop and Closed-loop Control. NIPS 1996: 1026-1032
18		Ron Papka, James P. Callan, Andrew G. Barto: Text-Based Information Retrieval Using Exponentiated Gradient Descent. NIPS 1996: 3-9
17		Steven J. Bradtke, Andrew G. Barto: Linear Least-Squares Algorithms for Temporal Difference Learning. Machine Learning 22(1-3): 33-57 (1996)
	1995
16		Robert H. Crites, Andrew G. Barto: Improving Elevator Performance Using Reinforcement Learning. NIPS 1995: 1017-1023
15		Andrew G. Barto, James C. Houk: A Predictive Switching Model of Cerebellar Movement Control. NIPS 1995: 138-144
14		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)
	1994
13		Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen: Learning Admittance Mappings for Force-Guided Assembly. ICRA 1994: 2633-2638
12		Robert H. Crites, Andrew G. Barto: An Actor/Critic Algorithm that is Equivalent to Q-Learning. NIPS 1994: 401-408
	1993
11		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
10		Satinder P. Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly: Robust Reinforcement Learning in Motion Planning. NIPS 1993: 655-662
9		Andrew G. Barto, Michael O. Duff: Monte Carlo Matrix Inversion and Reinforcement Learning. NIPS 1993: 687-694
8		Vijaykumar Gullapalli, Andrew G. Barto: Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms. NIPS 1993: 695-702
	1991
7		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
6		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)
5		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)
	1990
4		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
3		Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins: Sequential Decision Probelms and Neural Networks. NIPS 1989: 686-693
	1985
2		Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto: Training and Tracking in Robotics. IJCAI 1985: 670-672
	1978
1		Andrew G. Barto: A Note on Pattern Reproduction in Tessellation Structures. J. Comput. Syst. Sci. 16(3): 445-455 (1978)

Coauthor Index

1	Ivon Arroyo	[51] [60]
2	N. E. Berthier	[6] [7]
3	Steven J. Bradtke	[14] [17]
4	James P. Callan (Jamie Callan)	[18]
5	Nuttapong Chentanez	[43]
6	Christopher I. Connolly	[10]
7	Robert H. Crites	[12] [16] [22]
8	Toby Dragon	[60]
9	Michael O. Duff	[9] [20]
10	Richard E. A. Van Emmerik	[48]
11	Andrew H. Fagg	[25]
12	Kimberly Ferguson	[51] [60]
13	Don Fisher	[60]
14	Deepak Ganesan	[56]
15	Roderic A. Grupen	[10] [13] [69] [73] [75]
16	Vijaykumar Gullapalli	[8] [13]
17	Eric A. Hansen	[19]
18	James C. Houk	[7] [15] [25]
19	Robert A. Jacobs	[5] [11]
20	Jeffrey Johns	[60]
21	Anders Jonsson	[26] [47] [49] [57]
22	Michael I. Jordan	[5] [11]
23	George Konidaris	[50] [53] [58] [63] [64] [69] [75]
24	Michael Kositsky	[29] [34]
25	Scott Kuindersma	[69] [73] [75]
26	Richard L. Lewis	[66]
27	Sridhar Mahadevan	[39] [40] [51] [60]
28	Vimal Mathew	[59]
29	Amy McGovern	[33] [35]
30	Hasmik Meheranian	[60]
31	Robert Moll (Robert N. Moll)	[24] [28]
32	Jeffrey F. Monaco	[21]
33	J. W. Moore	[6]
34	J. Eliot B. Moss	[35]
35	Scott Niekum	[65] [70] [71] [74]
36	Ron Papka	[18]
37	Theodore J. Perkins	[24] [28] [31] [32] [36]
38	Marc Pickett	[38]
39	Jette Randløv	[27]
40	Balaraman Ravindran	[37] [41] [42] [59]
41	Michael T. Rosenstein	[27] [30] [48]
42	Sharad Saxena	[4]
43	Oliver G. Selfridge	[2]
44	Özgür Simsek	[44] [45] [46] [52] [61]
45	Satinder P. Singh	[7] [10] [14] [43] [66]
46	Nathan Sitkoff	[25]
47	Jonathan Sorg	[66]
48	Lee Spector	[65] [74]
49	Richard S. Sutton	[2] [3] [23] [24]
50	Philip Thomas	[72]
51	Paul E. Utgoff	[4]
52	Christopher M. Vigorito	[56] [62] [67]
53	David G. Ward	[21]
54	Christopher J. C. H. Watkins	[3]
55	Alicia P. Wolfe	[46] [54]
56	Beverly Park Woolf	[51] [60]
57	Richard C. Yee	[4]
58	Shlomo Zilberstein	[19]

Colors in the list of coauthors

Last update Sun May 27 04:04:01 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page