Year |
Citation |
Score |
2019 |
Santucci VG, Oudeyer PY, Barto A, Baldassarre G. Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots. Frontiers in Neurorobotics. 13: 115. PMID 32009927 DOI: 10.3389/fnbot.2019.00115 |
0.411 |
|
2019 |
Barto AG. Reinforcement Learning: Connections, Surprises, and Challenge Ai Magazine. 40: 3-15. DOI: 10.1609/AIMAG.V40I1.2844 |
0.369 |
|
2018 |
Frankenhuis WE, Panchanathan K, Barto AG. Enriching Behavioral Ecology with Reinforcement Learning Methods. Behavioural Processes. PMID 29412143 DOI: 10.1016/J.Beproc.2018.01.008 |
0.322 |
|
2015 |
Niekum S, Osentoski S, Konidaris G, Chitta S, Marthi B, Barto AG. Learning grounded finite-state representations from unstructured demonstrations International Journal of Robotics Research. 34: 131-157. DOI: 10.1177/0278364914554471 |
0.693 |
|
2015 |
Niekum S, Osentoski S, Atkeson CG, Barto AG. Online Bayesian changepoint detection for articulated motion models Proceedings - Ieee International Conference On Robotics and Automation. 2015: 1468-1475. DOI: 10.1109/ICRA.2015.7139383 |
0.505 |
|
2015 |
Botvinick M, Weinstein A, Solway A, Barto A. Reinforcement learning, efficient coding, and the statistics of natural tasks Current Opinion in Behavioral Sciences. 5: 71-77. DOI: 10.1016/J.Cobeha.2015.08.009 |
0.459 |
|
2014 |
Baldassarre G, Stafford T, Mirolli M, Redgrave P, Ryan RM, Barto A. Intrinsic motivations and open-ended development in animals, humans, and robots: an overview. Frontiers in Psychology. 5: 985. PMID 25249998 DOI: 10.3389/Fpsyg.2014.00985 |
0.394 |
|
2014 |
Da Silva BC, Baldassarre G, Konidaris G, Barto A. Learning parameterized motor skills on a humanoid robot Proceedings - Ieee International Conference On Robotics and Automation. 5239-5244. DOI: 10.1109/ICRA.2014.6907629 |
0.386 |
|
2014 |
Da Silva BC, Konidaris G, Barto A. Active learning of parameterized skills 31st International Conference On Machine Learning, Icml 2014. 5: 3736-3745. |
0.361 |
|
2013 |
Levy YZ, Levy DJ, Barto AG, Meyer JS. A computational hypothesis for allostasis: delineation of substance dependence, conventional therapies, and alternative treatments. Frontiers in Psychiatry. 4: 167. PMID 24391601 DOI: 10.3389/Fpsyt.2013.00167 |
0.709 |
|
2013 |
Barto A, Mirolli M, Baldassarre G. Novelty or surprise? Frontiers in Psychology. 4: 907. PMID 24376428 DOI: 10.3389/fpsyg.2013.00907 |
0.306 |
|
2013 |
Shah A, Barto AG, Fagg AH. A dual process account of coarticulation in motor skill acquisition. Journal of Motor Behavior. 45: 531-49. PMID 24116847 DOI: 10.1080/00222895.2013.837423 |
0.528 |
|
2013 |
Kuindersma SR, Grupen RA, Barto AG. Variable risk control via stochastic optimization International Journal of Robotics Research. 32: 806-825. DOI: 10.1177/0278364913476124 |
0.766 |
|
2013 |
Barto AG. Intrinsic motivation and reinforcement learning Intrinsically Motivated Learning in Natural and Artificial Systems. 17-47. DOI: 10.1007/978-3-642-32375-1_2 |
0.373 |
|
2013 |
Kuindersma S, Grupen R, Barto A. Variational Bayesian optimization for runtime risk-sensitive control Robotics: Science and Systems. 8: 201-208. |
0.609 |
|
2012 |
Konidaris G, Kuindersma S, Grupen R, Barto A. Robot learning from demonstration by constructing skill trees International Journal of Robotics Research. 31: 360-375. DOI: 10.1177/0278364911428653 |
0.762 |
|
2012 |
Niekum S, Osentoski S, Konidaris G, Barto AG. Learning and generalization of complex tasks from unstructured demonstrations Ieee International Conference On Intelligent Robots and Systems. 5239-5246. DOI: 10.1109/IROS.2012.6386006 |
0.348 |
|
2012 |
Konidaris G, Scheidwasser I, Barto AG. Transfer in reinforcement learning via shared features Journal of Machine Learning Research. 13: 1333-1371. |
0.306 |
|
2012 |
Da Silva BC, Konidaris G, Barto AG. Learning parameterized skills Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1679-1686. |
0.383 |
|
2012 |
Dabney W, Barto AG. Adaptive step-size for online temporal difference learning Proceedings of the National Conference On Artificial Intelligence. 2: 872-878. |
0.317 |
|
2011 |
Ribas-Fernandes JJ, Solway A, Diuk C, McGuire JT, Barto AG, Niv Y, Botvinick MM. A neural signature of hierarchical reinforcement learning. Neuron. 71: 370-9. PMID 21791294 DOI: 10.1016/J.Neuron.2011.05.042 |
0.361 |
|
2011 |
Niekum S, Spector L, Barto A. Evolution of reward functions for reinforcement learning Genetic and Evolutionary Computation Conference, Gecco'11 - Companion Publication. 177-178. DOI: 10.1145/2001858.2001957 |
0.331 |
|
2011 |
Kuindersma S, Grupen R, Barto A. Learning dynamic arm motions for postural recovery Ieee-Ras International Conference On Humanoid Robots. 7-12. DOI: 10.1109/Humanoids.2011.6100881 |
0.77 |
|
2011 |
Botvinick MM, Niv Y, Barto AG. Hierarchically organised behaviour and its neural foundations: A reinforcement-learning perspective Modelling Natural Action Selection. 264-299. DOI: 10.1017/CBO9780511731525.017 |
0.355 |
|
2011 |
Konidaris G, Kuindersma S, Grupen R, Barto A. Autonomous skill acquisition on a mobile manipulator Proceedings of the National Conference On Artificial Intelligence. 2: 1468-1473. |
0.599 |
|
2010 |
Konidaris G, Kuindersmay S, Barto A, Grupen R. Constructing skill trees for reinforcement learning agents from demonstration trajectories Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.662 |
|
2009 |
Shah A, Barto AG. Effect on movement selection of an evolving sensory representation: a multiple controller model of skill acquisition. Brain Research. 1299: 55-73. PMID 19595991 DOI: 10.1016/j.brainres.2009.07.006 |
0.543 |
|
2009 |
Botvinick MM, Niv Y, Barto AC. Hierarchically organized behavior and its neural foundations: a reinforcement learning perspective. Cognition. 113: 262-80. PMID 18926527 DOI: 10.1016/j.cognition.2008.08.011 |
0.388 |
|
2009 |
Konidaris G, Barto A. Skill discovery in continuous reinforcement learning domains using skill chaining Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1015-1023. |
0.324 |
|
2009 |
Konidaris G, Barto A. Efficient skill learning using abstraction selection Ijcai International Joint Conference On Artificial Intelligence. 1107-1112. |
0.343 |
|
2007 |
Konidaris G, Barto A. Building portable options: Skill transfer in reinforcement learning Ijcai International Joint Conference On Artificial Intelligence. 895-900. |
0.333 |
|
2006 |
Konidaris G, Barto A. Autonomous shaping: Knowledge transfer in reinforcement learning Acm International Conference Proceeding Series. 148: 489-496. DOI: 10.1145/1143844.1143906 |
0.325 |
|
2006 |
Rosenstein MT, Barto AG, Van Emmerik REA. Learning at the level of synergies for a robot weightlifter Robotics and Autonomous Systems. 54: 706-717. DOI: 10.1016/J.Robot.2006.03.002 |
0.773 |
|
2006 |
Wolfe AP, Barto AG. Decision tree methods for finding reusable MDP homomorphisms Proceedings of the National Conference On Artificial Intelligence. 1: 530-535. |
0.458 |
|
2005 |
Berthier NE, Rosenstein MT, Barto AG. Approximate optimal control as a model for motor learning. Psychological Review. 112: 329-46. PMID 15783289 DOI: 10.1037/0033-295X.112.2.329 |
0.747 |
|
2005 |
Singh S, Barto AG, Chentanez N. Intrinsically motivated reinforcement learning Advances in Neural Information Processing Systems. |
0.373 |
|
2005 |
Şimşek Ö, Wolfe AP, Barto AG. Identifying useful subgoals in reinforcement learning by local graph partitioning Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 817-824. |
0.594 |
|
2005 |
Şimşek O, Barto AG. Learning skills in reinforcement learning using relative novelty Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3607: 367-374. |
0.386 |
|
2004 |
Shah A, Fagg AH, Barto AG. Cortical involvement in the recruitment of wrist muscles. Journal of Neurophysiology. 91: 2445-56. PMID 14749314 DOI: 10.1152/Jn.00879.2003 |
0.394 |
|
2004 |
Rosenstein MT, Barto AG. Reinforcement learning with supervision by a stable controller Proceedings of the American Control Conference. 5: 4517-4522. DOI: 10.1109/ACC.2004.182663 |
0.753 |
|
2004 |
Şimşek O, Wolfe AP, Barto AG. Local graph partitioning as a basis for generating temporally-extended actions in reinforcement learning Aaai Workshop - Technical Report. 91-96. |
0.592 |
|
2004 |
Şimşek O, Barto AG. Using relative novelty to identify useful temporal abstractions in reinforcement learning Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 751-758. |
0.342 |
|
2003 |
Barto AG, Mahadevan S. Recent Advances in Hierarchical Reinforcement Learning Discrete Event Dynamic Systems: Theory and Applications. 13: 343-379+382. DOI: 10.1023/A:1022140919877 |
0.372 |
|
2003 |
Perkins TJ, Barto AG. Lyapunov design for safe reinforcement learning Journal of Machine Learning Research. 3: 803-832. |
0.636 |
|
2002 |
Fagg AH, Shah A, Barto AG. A computational model of muscle recruitment for wrist movements. Journal of Neurophysiology. 88: 3348-58. PMID 12466451 DOI: 10.1152/Jn.00621.2002 |
0.398 |
|
2002 |
Ravindran B, Barto AG. Model minimization in hierarchical reinforcement learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2371: 196-211. |
0.364 |
|
2001 |
Rosenstein MT, Barto AG. Robot weightlifting by direct policy search Ijcai International Joint Conference On Artificial Intelligence. 839-844. |
0.714 |
|
2001 |
Perkins TJ, Barto AG. Heuristic search in infinite state spaces guided by Lyapunov analysis Ijcai International Joint Conference On Artificial Intelligence. 242-247. |
0.511 |
|
1999 |
Moll R, Barto AG, Perkins TJ, Sutton RS. Learning instance-independent value functions to enhance local search Advances in Neural Information Processing Systems. 1017-1023. |
0.701 |
|
1998 |
Monaco JF, Ward DG, Barto AG. Automated aircraft recovery via reinforcement learning: Initial experiments Advances in Neural Information Processing Systems. 1022-1028. |
0.328 |
|
1998 |
Crites RH, Barto AG. Elevator Group Control Using Multiple Reinforcement Learning Agents Machine Learning. 12: 235-262. |
0.31 |
|
1997 |
Barto AG, Sutton RS. Chapter 19 Reinforcement learning in artificial intelligence Advances in Psychology. 121: 358-386. DOI: 10.1016/S0166-4115(97)80105-7 |
0.57 |
|
1997 |
Hansen EA, Barto AG, Zilberstein S. Reinforcement learning for mixed open-loop and closed-loop control Advances in Neural Information Processing Systems. 1026-1032. |
0.307 |
|
1997 |
Duff MO, Barto AG. Local bandit approximation for optimal learning problems Advances in Neural Information Processing Systems. 1019-1025. |
0.666 |
|
1994 |
Barto AG. Reinforcement learning control. Current Opinion in Neurobiology. 4: 888-93. PMID 7888773 DOI: 10.1016/0959-4388(94)90138-4 |
0.379 |
|
1994 |
Gullapalli V, Barto AG, Grupen RA. Learning admittance mappings for force-guided assembly Proceedings - Ieee International Conference On Robotics and Automation. 2633-2638. |
0.609 |
|
1992 |
Sutton RS, Barto AG, Williams RJ. Reinforcement Learning is Direct Adaptive Optimal Control Ieee Control Systems. 12: 19-22. DOI: 10.1109/37.126844 |
0.567 |
|
1992 |
Gullapalli V, Grupen RA, Barto AG. Learning reactive admittance control Proceedings - Ieee International Conference On Robotics and Automation. 2: 1475-1480. |
0.359 |
|
1991 |
Jacobs RA, Jordan MI, Barto AG. Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks Cognitive Science. 15: 219-250. DOI: 10.1016/0364-0213(91)80006-Q |
0.64 |
|
1986 |
Moore JW, Desmond JE, Berthier NE, Blazis DE, Sutton RS, Barto AG. Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element: response topography, neuronal firing, and interstimulus intervals. Behavioural Brain Research. 21: 143-54. PMID 3755947 DOI: 10.1016/0166-4328(86)90092-6 |
0.391 |
|
1985 |
Barto AG, Anandan P. Pattern-Recognizing Stochastic Learning Automata Ieee Transactions On Systems, Man and Cybernetics. 360-375. DOI: 10.1109/TSMC.1985.6313371 |
0.329 |
|
1983 |
Barto AG, Sutton RS, Anderson CW. Neuronlike Adaptive Elements That Can Solve Difficult Learning Control Problems Ieee Transactions On Systems, Man and Cybernetics. 834-846. DOI: 10.1109/TSMC.1983.6313077 |
0.536 |
|
1982 |
Barto AG, Anderson CW, Sutton RS. Synthesis of nonlinear control surfaces by a layered associative search network. Biological Cybernetics. 43: 175-85. PMID 7093360 DOI: 10.1007/BF00319977 |
0.48 |
|
1982 |
Barto AG, Sutton RS. Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element. Behavioural Brain Research. 4: 221-35. PMID 6277346 DOI: 10.1016/0166-4328(82)90001-8 |
0.386 |
|
1981 |
Barto AG, Sutton RS. Landmark learning: an illustration of associative search. Biological Cybernetics. 42: 1-8. PMID 7326277 DOI: 10.1007/BF00335152 |
0.518 |
|
1981 |
Sutton RS, Barto AG. Toward a modern theory of adaptive networks: expectation and prediction. Psychological Review. 88: 135-70. PMID 7291377 DOI: 10.1037/0033-295X.88.2.135 |
0.469 |
|
1979 |
Barto AG, Sutton RS, Brouwer PS. Associative search network: A reinforcement learning associative memory Biological Cybernetics. 40: 201-211. DOI: 10.1007/BF00453370 |
0.452 |
|
Show low-probability matches. |