Andrew G. Barto

111 papers A* 31A 2B 4C 1Journal 32Unranked 34

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Rediscovering Reinforcement Learning. Commun. ACM Andrew G. Barto
2021	J	`jnl`	Looking Back on the Actor-Critic Architecture. IEEE Trans. Syst. Man Cybern. Syst. Andrew G. Barto, Richard S. Sutton, Charles W. Anderson
2019	J	`jnl`	Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots. Frontiers Neurorobotics Vieri Giuliano Santucci, Pierre-Yves Oudeyer, Andrew G. Barto, Gianluca Baldassarre
2019	J	`jnl`	Reinforcement Learning: Connections, Surprises, and Challenge. AI Mag. Andrew G. Barto
2018	—	`book`	Reinforcement learning - an introduction, 2nd Edition. Richard S. Sutton, Andrew G. Barto
2017	—	`ch.`	Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning and Data Mining Andrew G. Barto
2017	J	`jnl`	On Ensuring that Intelligent Machines Are Well-Behaved. CoRR Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill
2015	J	`jnl`	Learning grounded finite-state representations from unstructured demonstrations. Int. J. Robotics Res. Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Sachin Chitta, Bhaskara Marthi, Andrew G. Barto
2015	A*	`conf`	Online Bayesian changepoint detection for articulated motion models. ICRA Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto
2014	A*	`conf`	Active Learning of Parameterized Skills. ICML Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
2014	J	`jnl`	Commentary on Utility and Bounds. Top. Cogn. Sci. Andrew G. Barto
2014	A*	`conf`	Learning parameterized motor skills on a humanoid robot. ICRA Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto
2014	J	`jnl`	Optimal Behavioral Hierarchy. PLoS Comput. Biol. Alec Solway, Carlos Diuk, Natalia Córdova, Debbie Yee, Andrew G. Barto, Yael Niv, Matthew M. Botvinick
2013	—	`ch.`	Behavioral Hierarchy: Exploration and Representation. Computational and Robotic Models of the Hierarchical Organization of Behavior Andrew G. Barto, George Dimitri Konidaris, Christopher M. Vigorito
2013	—	`conf`	Incremental Semantically Grounded Learning from Demonstration. Robotics: Science and Systems Scott Niekum, Sachin Chitta, Andrew G. Barto, Bhaskara Marthi, Sarah Osentoski
2013	—	`ch.`	Intrinsic Motivation and Reinforcement Learning. Intrinsically Motivated Learning in Natural and Artificial Systems Andrew G. Barto
2013	J	`jnl`	Variable risk control via stochastic optimization. Int. J. Robotics Res. Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
2012	A*	`conf`	Adaptive Step-Size for Online Temporal Difference Learning. AAAI William Dabney, Andrew G. Barto
2012	A*	`conf`	Learning Parameterized Skills. ICML Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
2012	A	`conf`	Learning and generalization of complex tasks from unstructured demonstrations. IROS Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto
2012	—	`conf`	Motor primitive discovery. ICDL-EPIROB Philip S. Thomas, Andrew G. Barto
2012	J	`jnl`	Robot learning from demonstration by constructing skill trees. Int. J. Robotics Res. George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
2012	A*	`conf`	TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI Bruno Castro da Silva, Andrew G. Barto
2012	J	`jnl`	Transfer in Reinforcement Learning via Shared Features. J. Mach. Learn. Res. George Dimitri Konidaris, Ilya Scheidwasser, Andrew G. Barto
2012	—	`conf`	Variational Bayesian Optimization for Runtime Risk-Sensitive Control. Robotics: Science and Systems Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
2011	A*	`conf`	Autonomous Skill Acquisition on a Mobile Manipulator. AAAI George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
2011	—	`conf`	Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Lifelong Learning Scott Niekum, Andrew G. Barto
2011	—	`conf`	Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. NIPS Scott Niekum, Andrew G. Barto
2011	A*	`conf`	Conjugate Markov Decision Processes. ICML Philip S. Thomas, Andrew G. Barto
2011	—	`conf`	Evolution of reward functions for reinforcement learning. GECCO (Companion) Scott Niekum, Lee Spector, Andrew G. Barto
2011	—	`conf`	Learning dynamic arm motions for postural recovery. Humanoids Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
2010	—	`ch.`	Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning Andrew G. Barto
2010	—	`conf`	Competence progress intrinsic motivation. ICDL Andrew Stout, Andrew G. Barto
2010	—	`conf`	Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories. NIPS George Dimitri Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen
2010	J	`jnl`	Genetic Programming for Reward Function Search. IEEE Trans. Auton. Ment. Dev. Scott Niekum, Andrew G. Barto, Lee Spector
2010	J	`jnl`	Intrinsically Motivated Hierarchical Skill Learning in Structured Environments. IEEE Trans. Auton. Ment. Dev. Christopher M. Vigorito, Andrew G. Barto
2010	J	`jnl`	Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective. IEEE Trans. Auton. Ment. Dev. Satinder Singh, Richard L. Lewis, Andrew G. Barto, Jonathan Sorg
2009	A*	`conf`	Efficient Skill Learning using Abstraction Selection. IJCAI George Dimitri Konidaris, Andrew G. Barto
2009	—	`conf`	Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining. NIPS George Dimitri Konidaris, Andrew G. Barto
2008	—	`conf`	Hierarchical Representations of Behavior for Efficient Creative Search. AAAI Spring Symposium: Creative Intelligent Systems Christopher M. Vigorito, Andrew G. Barto
2008	—	`conf`	Skill Characterization Based on Betweenness. NIPS Özgür Simsek, Andrew G. Barto
2007	—	`conf`	Active Learning of Dynamic Bayesian Networks in Markov Decision Processes. SARA Anders Jonsson, Andrew G. Barto
2007	B	`conf`	Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks. SECON Christopher M. Vigorito, Deepak Ganesan, Andrew G. Barto
2007	A*	`conf`	Building Portable Options: Skill Transfer in Reinforcement Learning. IJCAI George Dimitri Konidaris, Andrew G. Barto
2007	A*	`conf`	Deictic Option Schemas. IJCAI Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
2007	A	`conf`	Repairing Disengagement With Non-Invasive Interventions. AIED Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf
2007	J	`jnl`	Temporal difference learning. Scholarpedia Andrew G. Barto
2006	—	`conf`	An Adaptive Robot Motivational System. SAB George Dimitri Konidaris, Andrew G. Barto
2006	A*	`conf`	An intrinsic reward mechanism for efficient exploration. ICML Özgür Simsek, Andrew G. Barto
2006	A*	`conf`	Autonomous shaping: knowledge transfer in reinforcement learning. ICML George Dimitri Konidaris, Andrew G. Barto
2006	J	`jnl`	Causal Graph Based Decomposition of Factored MDPs. J. Mach. Learn. Res. Anders Jonsson, Andrew G. Barto
2006	A*	`conf`	Decision Tree Methods for Finding Reusable MDP Homomorphisms. AAAI Alicia P. Wolfe, Andrew G. Barto
2006	B	`conf`	Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. Intelligent Tutoring Systems Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto
2006	J	`jnl`	Learning at the level of synergies for a robot weightlifter. Robotics Auton. Syst. Michael T. Rosenstein, Andrew G. Barto, Richard E. A. Van Emmerik
2005	A*	`conf`	A causal approach to hierarchical decomposition of factored MDPs. ICML Anders Jonsson, Andrew G. Barto
2005	A*	`conf`	Identifying useful subgoals in reinforcement learning by local graph partitioning. ICML Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto
2005	—	`conf`	Learning Skills in Reinforcement Learning Using Relative Novelty. SARA Özgür Simsek, Andrew G. Barto
2004	—	`conf`	Intrinsically Motivated Reinforcement Learning. NIPS Satinder Singh, Andrew G. Barto, Nuttapong Chentanez
2004	B	`conf`	Reinforcement learning in the real world. IJCNN Andrew G. Barto
2004	C	`conf`	Reinforcement learning with supervision by a stable controller. ACC Michael T. Rosenstein, Andrew G. Barto
2004	A*	`conf`	Using relative novelty to identify useful temporal abstractions in reinforcement learning. ICML Özgür Simsek, Andrew G. Barto
2003	J	`jnl`	Recent Advances in Hierarchical Reinforcement Learning. Discret. Event Dyn. Syst. Andrew G. Barto, Sridhar Mahadevan
2003	J	`jnl`	Recent Advances in Hierarchical Reinforcement Learning. Discret. Event Dyn. Syst. Andrew G. Barto, Sridhar Mahadevan
2003	A*	`conf`	Relativized Options: Choosing the Right Transformation. ICML Balaraman Ravindran, Andrew G. Barto
2003	A*	`conf`	SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI Balaraman Ravindran, Andrew G. Barto
2002	J	`jnl`	Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts. Mach. Learn. Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
2002	J	`jnl`	Lyapunov Design for Safe Reinforcement Learning. J. Mach. Learn. Res. Theodore J. Perkins, Andrew G. Barto
2002	—	`conf`	Model Minimization in Hierarchical Reinforcement Learning. SARA Balaraman Ravindran, Andrew G. Barto
2002	A*	`conf`	PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. ICML Marc Pickett, Andrew G. Barto
2002	J	`jnl`	The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback. Neurocomputing Michael Kositsky, Andrew G. Barto
2001	A*	`conf`	Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. ICML Amy McGovern, Andrew G. Barto
2001	A*	`conf`	Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. IJCAI Theodore J. Perkins, Andrew G. Barto
2001	A*	`conf`	Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML Theodore J. Perkins, Andrew G. Barto
2001	A*	`conf`	Robot Weightlifting By Direct Policy Search. IJCAI Michael T. Rosenstein, Andrew G. Barto
2001	—	`conf`	The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. NIPS Michael Kositsky, Andrew G. Barto
2000	—	`conf`	Automated State Abstraction for Options using the U-Tree Algorithm. NIPS Anders Jonsson, Andrew G. Barto
2000	A*	`conf`	Combining Reinforcement Learning with a Local Control Algorithm. ICML Jette Randløv, Andrew G. Barto, Michael T. Rosenstein
2000	A*	`conf`	Machine Learning for Subproblem Selection. ICML Robert Moll, Theodore J. Perkins, Andrew G. Barto
1999	J	`jnl`	A Cerebellar Model of Timing and Prediction in the Control of Reaching. Neural Comput. Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk
1998	J	`jnl`	Elevator Group Control Using Multiple Reinforcement Learning Agents. Mach. Learn. Robert H. Crites, Andrew G. Barto
1998	—	`conf`	Learning Instance-Independent Value Functions to Enhance Local Search. NIPS Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton
1998	J	`jnl`	Reinforcement Learning: An Introduction. IEEE Trans. Neural Networks Richard S. Sutton, Andrew G. Barto
1998	—	`book`	Reinforcement learning - an introduction. Richard S. Sutton, Andrew G. Barto
1997	—	`conf`	A model of cerebellar learning for control of arm movements using muscle synergies. CIRA Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk
1997	—	`conf`	Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments. NIPS Jeffrey F. Monaco, David G. Ward, Andrew G. Barto
1997	A*	`conf`	Cerebellar learning for control of a two-link arm in muscle space. ICRA Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk
1996	J	`jnl`	Linear Least-Squares Algorithms for Temporal Difference Learning. Mach. Learn. Steven J. Bradtke, Andrew G. Barto
1996	—	`conf`	Local Bandit Approximation for Optimal Learning Problems. NIPS Michael O. Duff, Andrew G. Barto
1996	—	`conf`	Reinforcement Learning for Mixed Open-loop and Closed-loop Control. NIPS Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein
1996	—	`conf`	Text-Based Information Retrieval Using Exponentiated Gradient Descent. NIPS Ron Papka, James P. Callan, Andrew G. Barto
1995	—	`conf`	A Predictive Switching Model of Cerebellar Movement Control. NIPS Andrew G. Barto, James C. Houk
1995	—	`conf`	Improving Elevator Performance Using Reinforcement Learning. NIPS Robert H. Crites, Andrew G. Barto
1995	J	`jnl`	Learning to Act Using Real-Time Dynamic Programming. Artif. Intell. Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh
1994	—	`conf`	An Actor/Critic Algorithm that is Equivalent to Q-Learning. NIPS Robert H. Crites, Andrew G. Barto
1994	A*	`conf`	Learning Admittance Mappings for Force-Guided Assembly. ICRA Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen
1993	—	`conf`	Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms. NIPS Vijaykumar Gullapalli, Andrew G. Barto
1993	—	`conf`	Monte Carlo Matrix Inversion and Reinforcement Learning. NIPS Andrew G. Barto, Michael O. Duff
1993	—	`conf`	Robust Reinforcement Learning in Motion Planning. NIPS Satinder Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly
1993	—	`conf`	Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Machine Learning: From Theory to Applications Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
1992	A*	`conf`	Learning reactive admittance control. ICRA Vijaykumar Gullapalli, Roderic A. Grupen, Andrew G. Barto
1991	—	`conf`	A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm. NIPS N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk
1991	J	`jnl`	Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits. Biol. Cybern. N. E. Berthier, Andrew G. Barto, J. W. Moore
1991	J	`jnl`	Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Cogn. Sci. Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
1990	B	`conf`	Cerebellar control of endpoint position-a simulation model. IJCNN T. Sinkjaer, C. H. Wu, Andrew G. Barto, James C. Houk
1990	A*	`conf`	Explaining Temporal Differences to Create Useful Concepts for Evaluating States. AAAI Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew G. Barto
1989	—	`conf`	Sequential Decision Probelms and Neural Networks. NIPS Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins
1985	J	`jnl`	Pattern-recognizing stochastic learning automata. IEEE Trans. Syst. Man Cybern. Andrew G. Barto, P. Anandan
1985	A*	`conf`	Training and Tracking in Robotics. IJCAI Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto
1983	J	`jnl`	Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Trans. Syst. Man Cybern. Andrew G. Barto, Richard S. Sutton, Charles W. Anderson
1978	J	`jnl`	A Note on Pattern Reproduction in Tessellation Structures. J. Comput. Syst. Sci. Andrew G. Barto
1975	—	`—`	Cellular Automata As Models Of Natural Systems. Andrew G. Barto