Cognition Reversed : Robot Learning from Demonstration
暂无分享,去创建一个
[1] J. Konorski. Integrative activity of the brain , 1967 .
[2] Tai Sing Lee,et al. Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[3] Christian Balkenius,et al. Cognitive modeling with context sensitive reinforcement learning , 2004 .
[4] V. Braitenberg. Vehicles, Experiments in Synthetic Psychology , 1984 .
[5] G. Rizzolatti,et al. Motor facilitation during action observation: a magnetic stimulation study. , 1995, Journal of neurophysiology.
[6] S. C. Johnson. Hierarchical clustering schemes , 1967, Psychometrika.
[7] Aude Billard,et al. Learning human arm movements by imitation: : Evaluation of a biologically inspired connectionist architecture , 2000, Robotics Auton. Syst..
[8] K. Dautenhahn,et al. The correspondence problem , 2002 .
[9] A. Georgopoulos,et al. Modular organization of directionally tuned cells in the motor cortex: Is there a short-range order? , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[10] N. Logothetis,et al. Shape representation in the inferior temporal cortex of monkeys , 1995, Current Biology.
[11] Maja J. Matarić,et al. A framework for learning from demonstration, generalization and practice in human-robot domains , 2003 .
[12] B. Rohrer,et al. A learning and control approach based on the human neuromotor system , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..
[13] Henry Lieberman,et al. Watch what I do: programming by demonstration , 1993 .
[14] Maja J. Matarić,et al. Behavior-Based Segmentation of Demonstrated Task , 2006 .
[15] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[16] Ronald A. Howard,et al. Dynamic Programming and Markov Processes , 1960 .
[17] C. Gross. Genealogy of the “Grandmother Cell” , 2002, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[18] Karl J. Friston,et al. Free-energy and the brain , 2007, Synthese.
[19] John Demiris,et al. Movement imitation mechanisms in robots and humans , 1999 .
[20] Thomas Hellström,et al. Autonomous Forest Machines: Techniques and Algorithms for Unmanned Vehicles , 2008 .
[21] Leslie G. Ungerleider,et al. Neural correlates of category-specific knowledge , 1996, Nature.
[22] Karl J. Friston,et al. Predictive coding: an account of the mirror neuron system , 2007, Cognitive Processing.
[23] Yasuo Kuniyoshi,et al. Deferred imitation of human head movements by an active stereo vision head , 1997, Proceedings 6th IEEE International Workshop on Robot and Human Communication. RO-MAN'97 SENDAI.
[24] J. Hawkins,et al. On Intelligence , 2004 .
[25] Y. Demiris,et al. From motor babbling to hierarchical learning by imitation: a robot developmental pathway , 2005 .
[26] G. Rizzolatti,et al. Speech listening specifically modulates the excitability of tongue muscles: a TMS study , 2002, The European journal of neuroscience.
[27] Charles E. Connor. Neuroscience: Friends and grandmothers , 2005, Nature.
[28] L. S. Vygotskiĭ,et al. Mind in society : the development of higher psychological processes , 1978 .
[29] S. Wise,et al. Changes in motor cortical activity during visuomotor adaptation , 1998, Experimental Brain Research.
[30] R A Brooks,et al. New Approaches to Robotics , 1991, Science.
[31] Nils J. Nilsson,et al. APPLICATION OF INTELLIGENT AUTOMATA TO RECONNAISSANCE. , 1967 .
[32] Fabien Lagriffoul,et al. Activity Recognition Based on Intra and Extra Manipulation of Everyday Objects , 2007, UCS.
[33] E. Rolls,et al. View-invariant representations of familiar objects by neurons in the inferior temporal visual cortex. , 1998, Cerebral cortex.
[34] Aude Billard,et al. On Learning, Representing, and Generalizing a Task in a Humanoid Robot , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[35] Wolfram Burgard,et al. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .
[36] Rainer Bischoff,et al. Robotic Visions to 2020 and beyond -- The strategic research agenda for robotics in Europe , 2009 .
[37] Kerstin Dautenhahn,et al. Of hummingbirds and helicopters: An algebraic framework for interdisciplinary studies of imitation a , 2000 .
[38] Karl J. Friston. Functional integration and inference in the brain , 2002, Progress in Neurobiology.
[39] Herbert A. Simon,et al. The Sciences of the Artificial , 1970 .
[40] B. Rohrer,et al. S-Learning: A Biomimetic Algorithm for Learning, Memory, and Control in Robots , 2007, 2007 3rd International IEEE/EMBS Conference on Neural Engineering.
[41] S. Münch,et al. Robot Programming by Demonstration (RPD) - Using Machine Learning and User Interaction Methods for the Development of Easy and Comfortable Robot Programming Systems , 2000 .
[42] E. Vaadia,et al. Preparatory activity in motor cortex reflects learning of local visuomotor skills , 2003, Nature Neuroscience.
[43] Karl J. Friston,et al. A free energy principle for the brain , 2006, Journal of Physiology-Paris.
[44] R. Bellman,et al. Dynamic Programming and Markov Processes , 1960 .
[45] Rodney A. Brooks,et al. Elephants don't play chess , 1990, Robotics Auton. Syst..
[46] Yiannis Demiris,et al. Hierarchical attentive multiple models for execution and recognition of actions , 2006, Robotics Auton. Syst..
[47] Peter Bakker,et al. Robot see, robot do: An overview of robot imitation , 1996 .
[48] Dileep George,et al. Towards a Mathematical Theory of Cortical Micro-circuits , 2009, PLoS Comput. Biol..
[49] Fred Rothganger,et al. Model-Free Learning and Control in a Mobile Robot , 2009, 2009 Fifth International Conference on Natural Computation.
[50] Yiannis Demiris,et al. Perceiving the unusual: Temporal properties of hierarchical motor representations for action perception , 2006, Neural Networks.
[51] Chrystopher L. Nehaniv,et al. Action, State and Effect Metrics for Robot Imitation , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.
[52] Daniel M. Wolpert,et al. Forward Models for Physiological Motor Control , 1996, Neural Networks.
[53] K. Kaplan. H. Haken, Synergetics. An Introduction. Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry, and Biology (2nd Edition). XI + 355 S., 152 Abb. Berlin—Heidelberg—New York 1978. Springer-Verlag. DM 66,00 , 1980 .
[54] Yiannis Demiris,et al. Distributed, predictive perception of actions: a biologically inspired robotics architecture for imitation and learning , 2003, Connect. Sci..
[55] R. Dillmann,et al. TEACHING SERVICE ROBOTS COMPLEX TASKS : PROGRAMMING BY DEMONSTRATION FOR WORKSHOP AND HOUSEHOLD ENVIRONMENTS , 2001 .
[56] D. Wolpert,et al. Motor prediction , 2001, Current Biology.
[57] G. Rizzolatti,et al. A unifying view of the basis of social cognition , 2004, Trends in Cognitive Sciences.
[58] Fabien Lagriffoul,et al. Activity Recognition Using an Egocentric Perspective of Everyday Objects , 2007, UIC.
[59] Rodney A. Brooks,et al. Intelligence Without Reason , 1991, IJCAI.
[60] Maja J. Mataric,et al. Automated Derivation of Primitives for Movement Classification , 2000, Auton. Robots.
[61] Gillian M. Hayes,et al. A Robot Controller Using Learning by Imitation , 1994 .
[62] Christopher G. Atkeson,et al. Learning from observation using primitives , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).
[63] H. Haken. Synergetics: an Introduction, Nonequilibrium Phase Transitions and Self-organization in Physics, Chemistry, and Biology , 1977 .
[64] G. Rizzolatti,et al. Action recognition in the premotor cortex. , 1996, Brain : a journal of neurology.
[65] C. Sparrow. The Fractal Geometry of Nature , 1984 .
[66] Paul E. Utgoff,et al. Shift of bias for inductive concept learning , 1984 .
[67] Robin R. Murphy,et al. Introduction to AI Robotics , 2000 .
[68] Rüdiger Dillmann,et al. Building elementary robot skills from human demonstration , 1996, Proceedings of IEEE International Conference on Robotics and Automation.
[69] L. E. Berk,et al. Scaffolding Children's Learning: Vygotsky and Early Childhood Education. NAEYC Research into Practice Series. Volume 7. , 1995 .
[70] Zoubin Ghahramani,et al. Computational principles of movement neuroscience , 2000, Nature Neuroscience.
[71] Rolf Pfeifer,et al. Sensory - motor coordination: The metaphor and beyond , 1997, Robotics Auton. Syst..
[72] K. Dautenhahn,et al. Imitation in Animals and Artifacts , 2002 .
[73] Monica N. Nicolescu,et al. Natural methods for robot task learning: instructive demonstrations, generalization and practice , 2003, AAMAS '03.
[74] Brandon R. Rohrer. BECCA: A Brain Emulating Cognition and Control Architecture. , 2008 .
[75] Aude Billard,et al. Active Teaching in Robot Programming by Demonstration , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.
[76] W. Ashby,et al. Principles of the self-organizing dynamic system. , 1947, The Journal of general psychology.
[77] J. Mazziotta,et al. Cortical mechanisms of human imitation. , 1999, Science.
[78] Ronald C. Arkin,et al. An Behavior-based Robotics , 1998 .
[79] Jonathan Baxter,et al. Learning internal representations , 1995, COLT '95.
[80] Dana H. Ballard,et al. Recognizing teleoperated manipulations , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.
[81] Brandon Rohrer. S-Learning: A Model-Free, Case-Based Algorithm for Robot Learning and Control , 2009, ICCBR.
[82] Karl J. Friston. Learning and inference in the brain , 2003, Neural Networks.
[83] C. Keysers,et al. Towards a unifying neural theory of social cognition. , 2006, Progress in brain research.
[84] M. Matarić,et al. Behavior-Based Segmentation of Demonstrated Tasks , 2006 .
[85] M. Arbib,et al. Language within our grasp , 1998, Trends in Neurosciences.
[86] F. A. Mussa-lvaldi,et al. Convergent force fields organized in the frog's spinal cord , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[87] B. Bertenthal,et al. Does Perception of Biological Motion Rely on Specific Brain Regions? , 2001, NeuroImage.
[88] Michael I. Jordan,et al. Forward Models: Supervised Learning with a Distal Teacher , 1992, Cogn. Sci..
[89] Jay Hegdé,et al. Reappraising the Functional Implications of the Primate Visual Anatomical Hierarchy , 2007, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[90] Daniel M. Wolpert,et al. Hierarchical MOSAIC for movement generation , 2003 .
[91] Thomas Hellström,et al. A formalism for learning from demonstration , 2010, Paladyn J. Behav. Robotics.
[92] Stefan Schaal,et al. http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained , 2007 .
[93] Maja J. Mataric,et al. Designing and Understanding Adaptive Group Behavior , 1995, Adapt. Behav..
[94] Monica N. Nicolescu,et al. Experience-based representation construction: learning from human and robot teachers , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).
[95] C. Koch,et al. Invariant visual representation by single neurons in the human brain , 2005, Nature.
[96] A P Georgopoulos,et al. On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[97] Sebastian Thrun,et al. Learning to Learn , 1998, Springer US.
[98] Scott T. Grafton,et al. Premotor Cortex Activation during Observation and Naming of Familiar Tools , 1997, NeuroImage.
[99] Rolf Pfeifer,et al. Understanding intelligence , 2020, Inequality by Design.
[100] C. Gross. Brain, Vision, Memory: Tales in the History of Neuroscience , 1998 .
[101] Howard Hunt Pattee,et al. Hierarchy Theory: The Challenge of Complex Systems , 1973 .
[102] T. Poggio,et al. Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.
[103] Thomas Hellström,et al. Real-time path planning using a simulator-inthe-loop , 2009 .
[104] Aude Billard,et al. Reinforcement learning for imitating constrained reaching movements , 2007, Adv. Robotics.
[105] D. George,et al. A hierarchical Bayesian model of invariant pattern recognition in the visual cortex , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[106] D. Perrett,et al. Visual neurones responsive to faces in the monkey temporal cortex , 2004, Experimental Brain Research.
[107] Paul E. Utgoff,et al. On integrating apprentice learning and reinforcement learning , 1996 .
[108] Stuart A. Kauffman,et al. ORIGINS OF ORDER , 2019, Origins of Order.
[109] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[110] Richard Alan Peters,et al. Robonaut task learning through teleoperation , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).
[111] S. Ochs. Integrative Activity of the Brain: An Interdisciplinary Approach , 1968 .
[112] Larry A. Rendell,et al. Layered Concept-Learning and Dynamically Variable Bias Management , 1987, IJCAI.
[113] Stefan Schaal,et al. Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.
[114] V. Gallese. The manifold nature of interpersonal relations: the quest for a common mechanism. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[115] Brett Browning,et al. A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..
[116] G. Rizzolatti,et al. The mirror-neuron system. , 2004, Annual review of neuroscience.
[117] K. Doya,et al. A unifying computational framework for motor control and social interaction. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[118] Tomaso Poggio,et al. Generalization in vision and motor control , 2004, Nature.
[119] D M Wolpert,et al. Multiple paired forward and inverse models for motor control , 1998, Neural Networks.
[120] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[121] Nathan Delson,et al. Robot programming by human demonstration: the use of human inconsistency in improving 3D robot trajectories , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).
[122] Dileep George,et al. How the brain might work: a hierarchical and temporal model for learning and recognition , 2008 .
[123] Rodney A. Brooks,et al. A Robust Layered Control Syste For A Mobile Robot , 2022 .
[124] Chris Watkins,et al. Learning from delayed rewards , 1989 .
[125] Christian Balkenius,et al. Generalization and Specialization in Reinforcement Learning , 2007 .
[126] Chrystopher L. Nehaniv,et al. Imitation with ALICE: learning to imitate corresponding actions across dissimilar embodiments , 2002, IEEE Trans. Syst. Man Cybern. Part A.
[127] M. Kawato,et al. A hierarchical neural-network model for control and learning of voluntary movement , 2004, Biological Cybernetics.
[128] Mohammed Yeasin,et al. Toward automatic robot programming: learning human skill from visual data , 2000, IEEE Trans. Syst. Man Cybern. Part B.
[129] Werner,et al. Complexity in natural landform patterns , 1999, Science.
[130] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[131] Karl J. Friston. The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.
[132] Kazuhito Yokoi,et al. Recognition and Generation of Leg Primitive Motions for Dance Imitation by a Humanoid Robot , 2003 .
[133] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[134] Thomas Hellström,et al. Behavior recognition for segmentation of demonstrated tasks , 2008 .
[135] Juergen Schmidhuber,et al. A General Method For Incremental Self-Improvement And Multi-Agent Learning In Unrestricted Environme , 1999 .
[136] Mitsuo Kawato,et al. MOSAIC Model for Sensorimotor Learning and Control , 2001, Neural Computation.
[137] Y. Ho,et al. Simple Explanation of the No-Free-Lunch Theorem and Its Implications , 2002 .