Andrew G. Barto

James C. Houk, Nathan Sitkoff, Andrew H. Fagg, 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

Learning Parameterized Skills

Bruno Castro da Silva, Andrew G. Barto, George Konidaris, 2012, ICML.

Landmark learning: An illustration of associative search

Richard S. Sutton, Andrew G. Barto, R. Sutton, 1981, Biological Cybernetics.

Learning and generalization of complex tasks from unstructured demonstrations

Scott Niekum, Andrew G. Barto, George Konidaris, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

Andrew G. Barto, Deepak Ganesan, Christopher M. Vigorito, 2007, 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

Movements Under Resistive and Assistive Force Fields Encoding of Movement Dynamics by Purkinje Cell Simple Spike Activity During Fast Arm

Thomas Sinkjær, Mitsuo Kawato, Ashvin Shah, 2008 .

Recent Advances in Hierarchical Reinforcement Learning

Sridhar Mahadevan, Andrew G. Barto, A. Barto, 2003, Discret. Event Dyn. Syst..

Game-theoretic cooperativity in networks of self-interested units

Andrew G. Barto, A. Barto, 1987 .

Multiobjective Control Problems by Reinforcement Learning

Jennie Si, Andrew G. Barto, Don Wunsch, 2004 .

Transfer in Reinforcement Learning via Shared Features Citation

Andrew G. Barto, George Konidaris, Ilya Scheidwasser, 2012 .

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

James C. Houk, Nathan Sitkoff, Andrew H. Fagg, 1997, Proceedings of International Conference on Robotics and Automation.

Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining

Andrew G. Barto, George Konidaris, A. Barto, 2009, NIPS.

Cerebellar control of endpoint position-a simulation model

James C. Houk, Andrew G. Barto, C. H. Wu, 1990, 1990 IJCNN International Joint Conference on Neural Networks.

Variational Bayesian Optimization for Runtime Risk-Sensitive Control

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto, 2012, Robotics: Science and Systems.

TD-δπ: a model-free algorithm for efficient exploration

Bruno Castro da Silva, Andrew G. Barto, 2012, AAAI 2012.

Identifying useful subgoals in reinforcement learning by local graph partitioning

Alicia P. Wolfe, Andrew G. Barto, Özgür Simsek, 2005, ICML.

Evolution of reward functions for reinforcement learning

Lee Spector, Scott Niekum, Andrew G. Barto, 2011, GECCO.

Pattern-recognizing stochastic learning automata

P. Anandan, Andrew G. Barto, A. Barto, 1985, IEEE Transactions on Systems, Man, and Cybernetics.

Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto, 2010, NIPS.

Recent Advances in Hierarchical Reinforcement Learning

Sridhar Mahadevan, Andrew G. Barto, A. Barto, 2003, Discret. Event Dyn. Syst..

Learning admittance mappings for force-guided assembly

Roderic A. Grupen, Andrew G. Barto, Vijaykumar Gullapalli, 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

Using relative novelty to identify useful temporal abstractions in reinforcement learning

Andrew G. Barto, Özgür Simsek, A. Barto, 2004, ICML.

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

Shlomo Zilberstein, Eric A. Hansen, Andrew G. Barto, 1996, NIPS.

Learning Instance-Independent Value Functions to Enhance Local Search

Richard S. Sutton, Andrew G. Barto, Theodore J. Perkins, 1998, NIPS.

Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density

Andrew G. Barto, Amy McGovern, A. Barto, 2001, ICML.

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

Michael I. Jordan, Robert A. Jacobs, Andrew G. Barto, 1993, Machine Learning: From Theory to Applications.

Transfer in Reinforcement Learning via Shared Features

Andrew G. Barto, George Konidaris, Ilya Scheidwasser, 2012, J. Mach. Learn. Res..

Improving Elevator Performance Using Reinforcement Learning

Andrew G. Barto, Robert H. Crites, A. Barto, 1995, NIPS.

Autonomous shaping: knowledge transfer in reinforcement learning

Andrew G. Barto, George Konidaris, A. Barto, 2006, ICML.

Behavioral Hierarchy: Exploration and Representation

Andrew G. Barto, George Konidaris, Christopher M. Vigorito, 2013, Computational and Robotic Models of the Hierarchical Organization of Behavior.

Relativized Options: Choosing the Right Transformation

Balaraman Ravindran, Andrew G. Barto, A. Barto, 2003, ICML.

Enriching behavioral ecology with reinforcement learning methods

Andrew G. Barto, Willem E. Frankenhuis, Karthik Panchanathan, 2018, Behavioural Processes.

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

Andrew G. Barto, Marc Pickett, A. Barto, 2002, ICML.

Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts

Andrew G. Barto, J. Eliot B. Moss, Amy McGovern, 2002, Machine Learning.

Local Bandit Approximation for Optimal Learning Problems

Andrew G. Barto, Michael O. Duff, A. Barto, 1996, NIPS.

Robot learning from demonstration by constructing skill trees

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto, 2012, Int. J. Robotics Res..

An intrinsic reward mechanism for efficient exploration

Andrew G. Barto, Özgür Simsek, A. Barto, 2006, ICML.

Learning reactive admittance control

Roderic A. Grupen, Andrew G. Barto, Vijaykumar Gullapalli, 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

Behavioral building blocks for autonomous agents: description, identification, and learning

Andrew G. Barto, Özgür Simsek, A. Barto, 2008 .

Autonomous Skill Acquisition on a Mobile Manipulator

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto, 2011, AAAI.

Simulation of networks using multidimensional Fast Fourier Transforms

Andrew G. Barto, A. Barto, 1974, SIML.

Repairing Disengagement With Non-Invasive Interventions

Beverly Park Woolf, Sridhar Mahadevan, Andrew G. Barto, 2007, AIED.

Explaining Temporal Differences to Create Useful Concepts for Evaluating States

Paul E. Utgoff, Andrew G. Barto, Sharad Saxena, 1990, AAAI.

Reinforcement learning in motor control

Andrew G. Barto, A. Barto, 1998 .

Reinforcement learning control

Andrew G. Barto, A. Barto, 1994, Current Opinion in Neurobiology.

More models of the cerebellum

James C. Houk, Andrew G. Barto, A. Barto, 1996 .

Cellular automata as models of natural systems

Andrew G. Barto, A. Barto, 1975 .

Efficient skill learning using abstraction selection

Andrew G. Barto, George Konidaris, A. Barto, 2009, IJCAI 2009.

Where Do Rewards Come From

Richard L. Lewis, Andrew G. Barto, Satinder Singh, 2009 .

Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments

David G. Ward, Andrew G. Barto, Jeffrey F. Monaco, 1997, NIPS.

Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis

Andrew G. Barto, Theodore J. Perkins, A. Barto, 2001, IJCAI.

Learning grounded finite-state representations from unstructured demonstrations

Scott Niekum, Andrew G. Barto, George Konidaris, 2015, Int. J. Robotics Res..

On the Computational Economics of Reinforcement Learning

Andrew G. Barto, Satinder Singh, Satinder Singh, 1991 .

Learning Skills in Reinforcement Learning Using Relative Novelty

Andrew G. Barto, Özgür Simsek, A. Barto, 2005, SARA.

Building Portable Options: Skill Transfer in Reinforcement Learning

Andrew G. Barto, George Konidaris, A. Barto, 2007, IJCAI.

Adaptive Real-Time Dynamic Programming

Andrew G. Barto, A. Barto, 2017, Encyclopedia of Machine Learning and Data Mining.

Active Learning of Dynamic Bayesian Networks in Markov Decision Processes

Andrew G. Barto, Anders Jonsson, A. Barto, 2007, SARA.

Reinforcement Learning: An Introduction

Richard S. Sutton, Andrew G. Barto, R. Sutton, 1998, IEEE Trans. Neural Networks.

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

Andrew G. Barto, Robert H. Crites, A. Barto, 1994, NIPS.

Controlling a Nonlinear Spring-Mass System with a Cerebellar Model

James C. Houk, Andrew G. Barto, Jay T. Buckingham, 1994 .

An approach to learning control surfaces by connectionist systems

Andrew G. Barto, A. Barto, 1990 .

Training and Tracking in Robotics

Richard S. Sutton, Andrew G. Barto, Oliver G. Selfridge, 1985, IJCAI.

A Note on Pattern Reproduction in Tessellation Structures

Andrew G. Barto, A. Barto, 1978, J. Comput. Syst. Sci..

Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms

Andrew G. Barto, Vijaykumar Gullapalli, A. Barto, 1993, NIPS.

Intrinsically Motivated Reinforcement Learning: A Promising Framework for Developmental Robot Learning

Andrew G. Barto, George Konidaris, Andrew Stout, 2005 .

Learning dynamic arm motions for postural recovery

Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto, 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

Machine Learning for Subproblem Selection

Andrew G. Barto, Theodore J. Perkins, Robert Moll, 2000, ICML.

Connectionist learning for control

Andrew G. Barto, A. Barto, 1990 .

Handbook of Learning and Approximate Dynamic Programming (IEEE Press Series on Computational Intelligence)

Jennie Si, Andrew G. Barto, Don Wunsch, 2004 .

Online Bayesian changepoint detection for articulated motion models

Christopher G. Atkeson, Scott Niekum, Andrew G. Barto, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

A Predictive Switching Model of Cerebellar Movement Control

James C. Houk, Andrew G. Barto, A. Barto, 1995, NIPS.

Genetic Programming for Reward Function Search

Lee Spector, Scott Niekum, Andrew G. Barto, 2010, IEEE Transactions on Autonomous Mental Development.

Cooperative Interaction of Self-Interested Neuron-Like Processing Units

Andrew G. Barto, A. Barto, 1989 .

Goal Seeking Components for Adaptive Intelligence: An Initial Assessment.

Richard S. Sutton, Andrew G. Barto, R. Sutton, 1981 .

Learning as hill-climbing in weight space

Andrew G. Barto, A. Barto, 1998 .

Lyapunov-Constrained Action Sets for Reinforcement Learning

Andrew G. Barto, Theodore J. Perkins, A. Barto, 2001, ICML.

Neural Networks and Adaptive Control

Andrew G. Barto, Vijaykumar Gullapalli, A. Barto, 1993 .

Intrinsic Motivation and Reinforcement Learning

Andrew G. Barto, A. Barto, 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.

Learning parameterized motor skills on a humanoid robot

Bruno Castro da Silva, Andrew G. Barto, George Konidaris, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

On Ensuring that Intelligent Machines Are Well-Behaved pdf

Bruno Castro da Silva, Andrew G. Barto, Philip S. Thomas, 2017, ArXiv.

Motor programs and sensorimotor integration

Thomas Sinkjær, James C. Houk, Andrew G. Barto, 1990 .

Monte Carlo Matrix Inversion and Reinforcement Learning

Andrew G. Barto, Michael O. Duff, A. Barto, 1993, NIPS.

Incremental Semantically Grounded Learning from Demonstration

Scott Niekum, Andrew G. Barto, Sachin Chitta, 2013, Robotics: Science and Systems.

Intrinsically Motivated Reinforcement Learning

Nuttapong Chentanez, Andrew G. Barto, Satinder P. Singh, 2004, NIPS.

An Adaptive Sensorimotor Network Inspired by the Anatomy and Physiology

James C. Houk, Andrew G. Barto, Satinder Singh, 1989 .

Cooperativity in Networks of Pattern Recognizing Stochastic Learning Automata

P. Anandan, Andrew G. Barto, Charles W. Anderson, 1986 .

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

James C. Houk, Nathan Sitkoff, Andrew H. Fagg, 1999, Neural Computation.

Text-Based Information Retrieval Using Exponentiated Gradient Descent

James P. Callan, Andrew G. Barto, Ron Papka, 1996, NIPS.

DISCRETE AND CONTINUOUS MODELS

Andrew G. Barto, A. Barto, 1978 .

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

Bruno Castro da Silva, Andrew G. Barto, 2012, AAAI.

Causal Graph Based Decomposition of Factored MDPs

Andrew G. Barto, Anders Jonsson, A. Barto, 2006, J. Mach. Learn. Res..

Learning to Act Using Real-Time Dynamic Programming

Andrew G. Barto, Satinder P. Singh, Steven J. Bradtke, 1995, Artif. Intell..

Reinforcement Learning and Dynamic Programming

Andrew G. Barto, A. Barto, 1995 .

Generalization and Function Approximation

Richard S. Sutton, Andrew G. Barto, 1998 .

Learning as Hillclimbing in Weight Space

Andrew G. Barto, A. Barto, 2020 .

This Excerpt from Reinforcement Learning. Introduction 1.2 Examples 1.3 Elements of Reinforcement Learning 1.3 Elements of Reinforcement Learning

Richard S. Sutton, Andrew G. Barto, .

Betweenness Centrality as a Basis for Forming Skills Özgür Şimşek

Andrew G. Barto, A. Barto, 2007 .

Solutions to Selected Problems In : Reinforcement Learning : An Introduction by

Richard S. Sutton, Andrew G. Barto, 2008 .