Andrew G. Barto

According to our database, Andrew G. Barto authored at least 105 papers between 1978 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Looking Back on the Actor-Critic Architecture.

Andrew G. Barto, Richard S. Sutton, Charles W. Anderson

IEEE Trans. Syst. Man Cybern. Syst., 2021

2019

Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots.

Vieri Giuliano Santucci, Pierre-Yves Oudeyer, Andrew G. Barto, Gianluca Baldassarre

Frontiers Neurorobotics, 2019

Reinforcement Learning: Connections, Surprises, and Challenge.

Andrew G. Barto

AI Mag., 2019

2017

Adaptive Real-Time Dynamic Programming.

Andrew G. Barto

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

On Ensuring that Intelligent Machines Are Well-Behaved.

Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill

CoRR, 2017

2015

Learning grounded finite-state representations from unstructured demonstrations.

Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Sachin Chitta, Bhaskara Marthi, Andrew G. Barto

Int. J. Robotics Res., 2015

Online Bayesian changepoint detection for articulated motion models.

Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Commentary on Utility and Bounds.

Andrew G. Barto

Top. Cogn. Sci., 2014

Optimal Behavioral Hierarchy.

Alec Solway, Carlos Diuk, Natalia Córdova, Debbie Yee, Andrew G. Barto, Yael Niv, Matthew M. Botvinick

PLoS Comput. Biol., 2014

Learning parameterized motor skills on a humanoid robot.

Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Active Learning of Parameterized Skills.

Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Variable risk control via stochastic optimization.

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto

Int. J. Robotics Res., 2013

Incremental Semantically Grounded Learning from Demonstration.

Scott Niekum, Sachin Chitta, Andrew G. Barto, Bhaskara Marthi, Sarah Osentoski

Proceedings of the Robotics: Science and Systems IX, Technische Universität Berlin, Berlin, Germany, June 24, 2013

Intrinsic Motivation and Reinforcement Learning.

Andrew G. Barto

Proceedings of the Intrinsically Motivated Learning in Natural and Artificial Systems, 2013

Behavioral Hierarchy: Exploration and Representation.

Andrew G. Barto, George Dimitri Konidaris, Christopher M. Vigorito

Proceedings of the Computational and Robotic Models of the Hierarchical Organization of Behavior, 2013

2012

Transfer in Reinforcement Learning via Shared Features.

George Dimitri Konidaris, Ilya Scheidwasser, Andrew G. Barto

J. Mach. Learn. Res., 2012

Robot learning from demonstration by constructing skill trees.

George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto

Int. J. Robotics Res., 2012

Variational Bayesian Optimization for Runtime Risk-Sensitive Control.

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto

Proceedings of the Robotics: Science and Systems VIII, 2012

Learning and generalization of complex tasks from unstructured demonstrations.

Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

Learning Parameterized Skills.

Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 29th International Conference on Machine Learning, 2012

Motor primitive discovery.

Philip S. Thomas, Andrew G. Barto

Proceedings of the 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, 2012

TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration.

Bruno Castro da Silva, Andrew G. Barto

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

Adaptive Step-Size for Online Temporal Difference Learning.

William Dabney, Andrew G. Barto

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Conjugate Markov Decision Processes.

Philip S. Thomas, Andrew G. Barto

Proceedings of the 28th International Conference on Machine Learning, 2011

Learning dynamic arm motions for postural recovery.

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto

Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2011), 2011

Evolution of reward functions for reinforcement learning.

Scott Niekum, Lee Spector, Andrew G. Barto

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery.

Scott Niekum, Andrew G. Barto

Proceedings of the Lifelong Learning, 2011

Autonomous Skill Acquisition on a Mobile Manipulator.

George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Adaptive Real-Time Dynamic Programming.

Andrew G. Barto

Proceedings of the Encyclopedia of Machine Learning, 2010

Intrinsically Motivated Hierarchical Skill Learning in Structured Environments.

Christopher M. Vigorito, Andrew G. Barto

IEEE Trans. Auton. Ment. Dev., 2010

Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective.

Satinder Singh, Richard L. Lewis, Andrew G. Barto, Jonathan Sorg

IEEE Trans. Auton. Ment. Dev., 2010

Genetic Programming for Reward Function Search.

Scott Niekum, Andrew G. Barto, Lee Spector

IEEE Trans. Auton. Ment. Dev., 2010

Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories.

George Dimitri Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Competence progress intrinsic motivation.

Andrew Stout, Andrew G. Barto

Proceedings of the 2010 IEEE 9th International Conference on Development and Learning, 2010

2009

Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining.

George Dimitri Konidaris, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Efficient Skill Learning using Abstraction Selection.

George Dimitri Konidaris, Andrew G. Barto

Proceedings of the IJCAI 2009, 2009

2008

Skill Characterization Based on Betweenness.

Özgür Simsek, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Hierarchical Representations of Behavior for Efficient Creative Search.

Christopher M. Vigorito, Andrew G. Barto

Proceedings of the Creative Intelligent Systems, 2008

2007

Temporal difference learning.

Andrew G. Barto

Scholarpedia, 2007

Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks.

Christopher M. Vigorito, Deepak Ganesan, Andrew G. Barto

Proceedings of the Fourth Annual IEEE Communications Society Conference on Sensor, 2007

Active Learning of Dynamic Bayesian Networks in Markov Decision Processes.

Anders Jonsson, Andrew G. Barto

Proceedings of the Abstraction, 2007

Deictic Option Schemas.

Balaraman Ravindran, Andrew G. Barto, Vimal Mathew

Proceedings of the IJCAI 2007, 2007

Building Portable Options: Skill Transfer in Reinforcement Learning.

George Dimitri Konidaris, Andrew G. Barto

Proceedings of the IJCAI 2007, 2007

Repairing Disengagement With Non-Invasive Interventions.

Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf

Proceedings of the Artificial Intelligence in Education, 2007

2006

Learning at the level of synergies for a robot weightlifter.

Michael T. Rosenstein, Andrew G. Barto, Richard E. A. Van Emmerik

Robotics Auton. Syst., 2006

Causal Graph Based Decomposition of Factored MDPs.

Anders Jonsson, Andrew G. Barto

J. Mach. Learn. Res., 2006

An Adaptive Robot Motivational System.

George Dimitri Konidaris, Andrew G. Barto

Proceedings of the From Animals to Animats 9, 2006

Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels.

Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto

Proceedings of the Intelligent Tutoring Systems, 8th International Conference, 2006

An intrinsic reward mechanism for efficient exploration.

Özgür Simsek, Andrew G. Barto

Proceedings of the Machine Learning, 2006

Autonomous shaping: knowledge transfer in reinforcement learning.

George Dimitri Konidaris, Andrew G. Barto

Proceedings of the Machine Learning, 2006

Decision Tree Methods for Finding Reusable MDP Homomorphisms.

Alicia P. Wolfe, Andrew G. Barto

Proceedings of the Proceedings, 2006

2005

Learning Skills in Reinforcement Learning Using Relative Novelty.

Özgür Simsek, Andrew G. Barto

Proceedings of the Abstraction, 2005

Identifying useful subgoals in reinforcement learning by local graph partitioning.

Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto

Proceedings of the Machine Learning, 2005

A causal approach to hierarchical decomposition of factored MDPs.

Anders Jonsson, Andrew G. Barto

Proceedings of the Machine Learning, 2005

2004

Intrinsically Motivated Reinforcement Learning.

Satinder Singh, Andrew G. Barto, Nuttapong Chentanez

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Using relative novelty to identify useful temporal abstractions in reinforcement learning.

Özgür Simsek, Andrew G. Barto

Proceedings of the Machine Learning, 2004

Reinforcement learning with supervision by a stable controller.

Michael T. Rosenstein, Andrew G. Barto

Proceedings of the 2004 American Control Conference, 2004

2003

Recent Advances in Hierarchical Reinforcement Learning.

Andrew G. Barto, Sridhar Mahadevan

Discret. Event Dyn. Syst., 2003

SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes.

Balaraman Ravindran, Andrew G. Barto

Proceedings of the IJCAI-03, 2003

Relativized Options: Choosing the Right Transformation.

Balaraman Ravindran, Andrew G. Barto

Proceedings of the Machine Learning, 2003

2002

Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts.

Amy McGovern, J. Eliot B. Moss, Andrew G. Barto

Mach. Learn., 2002

Lyapunov Design for Safe Reinforcement Learning.

Theodore J. Perkins, Andrew G. Barto

J. Mach. Learn. Res., 2002

The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback.

Michael Kositsky, Andrew G. Barto

Neurocomputing, 2002

Model Minimization in Hierarchical Reinforcement Learning.

Balaraman Ravindran, Andrew G. Barto

Proceedings of the Abstraction, 2002

PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning.

Marc Pickett, Andrew G. Barto

Proceedings of the Machine Learning, 2002

2001

The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay.

Michael Kositsky, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Robot Weightlifting By Direct Policy Search.

Michael T. Rosenstein, Andrew G. Barto

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis.

Theodore J. Perkins, Andrew G. Barto

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Lyapunov-Constrained Action Sets for Reinforcement Learning.

Theodore J. Perkins, Andrew G. Barto

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density.

Amy McGovern, Andrew G. Barto

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000

Automated State Abstraction for Options using the U-Tree Algorithm.

Anders Jonsson, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Combining Reinforcement Learning with a Local Control Algorithm.

Jette Randløv, Andrew G. Barto, Michael T. Rosenstein

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Machine Learning for Subproblem Selection.

Robert Moll, Theodore J. Perkins, Andrew G. Barto

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999

A Cerebellar Model of Timing and Prediction in the Control of Reaching.

Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk

Neural Comput., 1999

1998

Reinforcement Learning: An Introduction.

Richard S. Sutton, Andrew G. Barto

IEEE Trans. Neural Networks, 1998

Elevator Group Control Using Multiple Reinforcement Learning Agents.

Robert H. Crites, Andrew G. Barto

Mach. Learn., 1998

Learning Instance-Independent Value Functions to Enhance Local Search.

Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Reinforcement learning - an introduction.

Richard S. Sutton, Andrew G. Barto

Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-19398-6, 1998

1997

Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments.

Jeffrey F. Monaco, David G. Ward, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Cerebellar learning for control of a two-link arm in muscle space.

Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk

Proceedings of the 1997 IEEE International Conference on Robotics and Automation, 1997

A model of cerebellar learning for control of arm movements using muscle synergies.

Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk

Proceedings of the Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97, 1997

1996

Linear Least-Squares Algorithms for Temporal Difference Learning.

Steven J. Bradtke, Andrew G. Barto

Mach. Learn., 1996

Text-Based Information Retrieval Using Exponentiated Gradient Descent.

Ron Papka, James P. Callan, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Reinforcement Learning for Mixed Open-loop and Closed-loop Control.

Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Local Bandit Approximation for Optimal Learning Problems.

Michael O. Duff, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995

Learning to Act Using Real-Time Dynamic Programming.

Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh

Artif. Intell., 1995

Improving Elevator Performance Using Reinforcement Learning.

Robert H. Crites, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

A Predictive Switching Model of Cerebellar Movement Control.

Andrew G. Barto, James C. Houk

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994

An Actor/Critic Algorithm that is Equivalent to Q-Learning.

Robert H. Crites, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Learning Admittance Mappings for Force-Guided Assembly.

Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen

Proceedings of the 1994 International Conference on Robotics and Automation, 1994

1993

Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks.

Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto

Proceedings of the Machine Learning: From Theory to Applications, 1993

Robust Reinforcement Learning in Motion Planning.

Satinder Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms.

Vijaykumar Gullapalli, Andrew G. Barto

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Monte Carlo Matrix Inversion and Reinforcement Learning.

Andrew G. Barto, Michael O. Duff

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

Learning reactive admittance control.

Vijaykumar Gullapalli, Roderic A. Grupen, Andrew G. Barto

Proceedings of the 1992 IEEE International Conference on Robotics and Automation, 1992

1991

Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks.

Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto

Cogn. Sci., 1991

Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits.

N. E. Berthier, Andrew G. Barto, J. W. Moore

Biol. Cybern., 1991

A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm.

N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990

Cerebellar control of endpoint position-a simulation model.

T. Sinkjaer, C. H. Wu, Andrew G. Barto, James C. Houk

Proceedings of the IJCNN 1990, 1990

Explaining Temporal Differences to Create Useful Concepts for Evaluating States.

Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew G. Barto

Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29, 1990

1989

Sequential Decision Probelms and Neural Networks.

Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins

Proceedings of the Advances in Neural Information Processing Systems 2, 1989

1985

Pattern-recognizing stochastic learning automata.

Andrew G. Barto, P. Anandan

IEEE Trans. Syst. Man Cybern., 1985

Training and Tracking in Robotics.

Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto

Proceedings of the 9th International Joint Conference on Artificial Intelligence. Los Angeles, 1985

1983

Neuronlike adaptive elements that can solve difficult learning control problems.

Andrew G. Barto, Richard S. Sutton, Charles W. Anderson

IEEE Trans. Syst. Man Cybern., 1983

1978

A Note on Pattern Reproduction in Tessellation Structures.

Andrew G. Barto

J. Comput. Syst. Sci., 1978