2008 |
60 | EE | Özgür Simsek,
Andrew G. Barto:
Skill Characterization Based on Betweenness.
NIPS 2008: 1497-1504 |
2007 |
59 | | 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 |
58 | EE | Balaraman Ravindran,
Andrew G. Barto,
Vimal Mathew:
Deictic Option Schemas.
IJCAI 2007: 1023-1028 |
57 | EE | George Konidaris,
Andrew G. Barto:
Building Portable Options: Skill Transfer in Reinforcement Learning.
IJCAI 2007: 895-900 |
56 | EE | Anders Jonsson,
Andrew G. Barto:
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes.
SARA 2007: 273-284 |
55 | EE | Christopher M. Vigorito,
Deepak Ganesan,
Andrew G. Barto:
Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks.
SECON 2007: 21-30 |
54 | EE | Andrew G. Barto:
Temporal difference learning.
Scholarpedia 2(11): 1604 (2007) |
2006 |
53 | | Alicia P. Wolfe,
Andrew G. Barto:
Decision Tree Methods for Finding Reusable MDP Homomorphisms.
AAAI 2006 |
52 | EE | George Konidaris,
Andrew G. Barto:
Autonomous shaping: knowledge transfer in reinforcement learning.
ICML 2006: 489-496 |
51 | EE | Özgür Simsek,
Andrew G. Barto:
An intrinsic reward mechanism for efficient exploration.
ICML 2006: 833-840 |
50 | EE | 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 |
49 | EE | George Konidaris,
Andrew G. Barto:
An Adaptive Robot Motivational System.
SAB 2006: 346-356 |
48 | EE | Anders Jonsson,
Andrew G. Barto:
Causal Graph Based Decomposition of Factored MDPs.
Journal of Machine Learning Research 7: 2259-2301 (2006) |
47 | EE | 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 |
46 | EE | Anders Jonsson,
Andrew G. Barto:
A causal approach to hierarchical decomposition of factored MDPs.
ICML 2005: 401-408 |
45 | EE | Özgür Simsek,
Alicia P. Wolfe,
Andrew G. Barto:
Identifying useful subgoals in reinforcement learning by local graph partitioning.
ICML 2005: 816-823 |
44 | EE | Özgür Simsek,
Andrew G. Barto:
Learning Skills in Reinforcement Learning Using Relative Novelty.
SARA 2005: 367-374 |
2004 |
43 | EE | Özgür Simsek,
Andrew G. Barto:
Using relative novelty to identify useful temporal abstractions in reinforcement learning.
ICML 2004 |
42 | EE | Satinder P. Singh,
Andrew G. Barto,
Nuttapong Chentanez:
Intrinsically Motivated Reinforcement Learning.
NIPS 2004 |
2003 |
41 | | Balaraman Ravindran,
Andrew G. Barto:
Relativized Options: Choosing the Right Transformation.
ICML 2003: 608-615 |
40 | | Balaraman Ravindran,
Andrew G. Barto:
SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes.
IJCAI 2003: 1011-1018 |
39 | EE | Andrew G. Barto,
Sridhar Mahadevan:
Recent Advances in Hierarchical Reinforcement Learning.
Discrete Event Dynamic Systems 13(1-2): 41-77 (2003) |
38 | EE | Andrew G. Barto,
Sridhar Mahadevan:
Recent Advances in Hierarchical Reinforcement Learning.
Discrete Event Dynamic Systems 13(4): 341-379 (2003) |
2002 |
37 | | Marc Pickett,
Andrew G. Barto:
PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning.
ICML 2002: 506-513 |
36 | EE | Balaraman Ravindran,
Andrew G. Barto:
Model Minimization in Hierarchical Reinforcement Learning.
SARA 2002: 196-211 |
35 | EE | Theodore J. Perkins,
Andrew G. Barto:
Lyapunov Design for Safe Reinforcement Learning.
Journal of Machine Learning Research 3: 803-832 (2002) |
34 | | 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) |
33 | EE | 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 |
32 | | Amy McGovern,
Andrew G. Barto:
Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density.
ICML 2001: 361-368 |
31 | | Theodore J. Perkins,
Andrew G. Barto:
Lyapunov-Constrained Action Sets for Reinforcement Learning.
ICML 2001: 409-416 |
30 | | Theodore J. Perkins,
Andrew G. Barto:
Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis.
IJCAI 2001: 242-247 |
29 | | Michael T. Rosenstein,
Andrew G. Barto:
Robot Weightlifting By Direct Policy Search.
IJCAI 2001: 839-846 |
28 | EE | Michael Kositsky,
Andrew G. Barto:
The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay.
NIPS 2001: 43-50 |
2000 |
27 | | Robert Moll,
Theodore J. Perkins,
Andrew G. Barto:
Machine Learning for Subproblem Selection.
ICML 2000: 615-622 |
26 | | Jette Randløv,
Andrew G. Barto,
Michael T. Rosenstein:
Combining Reinforcement Learning with a Local Control Algorithm.
ICML 2000: 775-782 |
25 | | Anders Jonsson,
Andrew G. Barto:
Automated State Abstraction for Options using the U-Tree Algorithm.
NIPS 2000: 1054-1060 |
1999 |
24 | | 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 |
23 | EE | Robert Moll,
Andrew G. Barto,
Theodore J. Perkins,
Richard S. Sutton:
Learning Instance-Independent Value Functions to Enhance Local Search.
NIPS 1998: 1017-1023 |
22 | EE | Richard S. Sutton,
Andrew G. Barto:
Reinforcement Learning: An Introduction.
IEEE Transactions on Neural Networks 9(5): 1054-1054 (1998) |
21 | | Robert H. Crites,
Andrew G. Barto:
Elevator Group Control Using Multiple Reinforcement Learning Agents.
Machine Learning 33(2-3): 235-262 (1998) |
1997 |
20 | | Jeffrey F. Monaco,
David G. Ward,
Andrew G. Barto:
Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments.
NIPS 1997 |
1996 |
19 | EE | Michael O. Duff,
Andrew G. Barto:
Local Bandit Approximation for Optimal Learning Problems.
NIPS 1996: 1019-1025 |
18 | EE | Eric A. Hansen,
Andrew G. Barto,
Shlomo Zilberstein:
Reinforcement Learning for Mixed Open-loop and Closed-loop Control.
NIPS 1996: 1026-1032 |
17 | EE | Ron Papka,
James P. Callan,
Andrew G. Barto:
Text-Based Information Retrieval Using Exponentiated Gradient Descent.
NIPS 1996: 3-9 |
16 | | Steven J. Bradtke,
Andrew G. Barto:
Linear Least-Squares Algorithms for Temporal Difference Learning.
Machine Learning 22(1-3): 33-57 (1996) |
1995 |
15 | EE | Robert H. Crites,
Andrew G. Barto:
Improving Elevator Performance Using Reinforcement Learning.
NIPS 1995: 1017-1023 |
14 | EE | Andrew G. Barto,
James C. Houk:
A Predictive Switching Model of Cerebellar Movement Control.
NIPS 1995: 138-144 |
13 | EE | 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 |
12 | | Vijaykumar Gullapalli,
Andrew G. Barto,
Roderic A. Grupen:
Learning Admittance Mappings for Force-Guided Assembly.
ICRA 1994: 2633-2638 |
11 | EE | Robert H. Crites,
Andrew G. Barto:
An Actor/Critic Algorithm that is Equivalent to Q-Learning.
NIPS 1994: 401-408 |
1993 |
10 | | 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 |
9 | EE | Satinder P. Singh,
Andrew G. Barto,
Roderic A. Grupen,
Christopher I. Connolly:
Robust Reinforcement Learning in Motion Planning.
NIPS 1993: 655-662 |
8 | EE | Andrew G. Barto,
Michael O. Duff:
Monte Carlo Matrix Inversion and Reinforcement Learning.
NIPS 1993: 687-694 |
7 | EE | Vijaykumar Gullapalli,
Andrew G. Barto:
Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms.
NIPS 1993: 695-702 |
1991 |
6 | EE | 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 |
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 | EE | 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) |