Imitation Learning
暂无分享,去创建一个
Mohamed Medhat Gaber | Eyad Elyan | Chrisina Jayne | Ahmed Hussein | A. Hussein | M. Gaber | Eyad Elyan | Chrisina Jayne
[1] 共立出版株式会社. コンピュータ・サイエンス : ACM computing surveys , 1978 .
[2] Long Ji Lin,et al. Programming Robots Using Reinforcement Learning and Teaching , 1991, AAAI.
[3] Claude Sammut,et al. Learning to Fly , 1992, ML.
[4] Gavriel Salomon,et al. T RANSFER OF LEARNING , 1992 .
[5] Dana H. Ballard,et al. Recognizing teleoperated manipulations , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.
[6] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[7] Peter Bakker,et al. Robot see, robot do: An overview of robot imitation , 1996 .
[8] Frédéric Gruau,et al. Cellular Encoding for interactive evolutionary robotics , 1996 .
[9] Dean A. Pomerleau,et al. Neural Network Vision for Robot Driving , 1997 .
[10] Phil Husbands,et al. Evolutionary robotics , 2014, Evolutionary Intelligence.
[11] Ran,et al. The correspondence problem , 1998 .
[12] Preben Alstrøm,et al. Learning to Drive a Bicycle Using Reinforcement Learning and Shaping , 1998, ICML.
[13] Andrew Y. Ng,et al. Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping , 1999, ICML.
[14] Craig Boutilier,et al. Implicit Imitation in Multiagent Reinforcement Learning , 1999, ICML.
[15] Stefan Schaal,et al. Is imitation learning the route to humanoid robots? , 1999, Trends in Cognitive Sciences.
[16] Maja J. Mataric,et al. Getting Humanoids to Move and Imitate , 2000, IEEE Intell. Syst..
[17] D. Floreano,et al. Evolutionary Robotics: The Biology,Intelligence,and Technology , 2000 .
[18] Aude Billard,et al. Learning human arm movements by imitation: : Evaluation of a biologically inspired connectionist architecture , 2000, Robotics Auton. Syst..
[19] Jun Nakanishi,et al. Learning Attractor Landscapes for Learning Motor Primitives , 2002, NIPS.
[20] Jun Nakanishi,et al. Learning rhythmic movements by demonstration using nonlinear oscillators , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.
[21] Benjamin Geisler,et al. An Empirical Study of Machine Learning Algorithms Applied to Modeling Player Behavior in a "First Person Shooter" Video Game , 2002 .
[22] Maja J. Matarić,et al. Sensory-motor primitives as a basis for imitation: linking perception to action and biology to robotics , 2002 .
[23] Michael A. Arbib,et al. Schema design and implementation of the grasp-related mirror neuron system , 2002, Biological Cybernetics.
[24] K. Dautenhahn,et al. The correspondence problem , 2002 .
[25] Stefan Schaal,et al. Computational approaches to motor learning by imitation. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[26] Yoav Shoham,et al. Multi-Agent Reinforcement Learning:a critical survey , 2003 .
[27] Peter Norvig,et al. Artificial intelligence - a modern approach, 2nd Edition , 2003, Prentice Hall series in artificial intelligence.
[28] Monica N. Nicolescu,et al. Natural methods for robot task learning: instructive demonstrations, generalization and practice , 2003, AAMAS '03.
[29] Gordon Cheng,et al. Learning tasks from observation and practice , 2004, Robotics Auton. Syst..
[30] Pradeep K. Khosla,et al. Learning by observation with mobile robots: a computational approach , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.
[31] Peter Stone,et al. Policy gradient reinforcement learning for fast quadrupedal locomotion , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.
[32] Ben Tse,et al. Autonomous Inverted Helicopter Flight via Reinforcement Learning , 2004, ISER.
[33] Jun Morimoto,et al. Learning from demonstration and adaptation of biped locomotion , 2004, Robotics Auton. Syst..
[34] Long Ji Lin,et al. Self-improving reactive agents based on reinforcement learning, planning and teaching , 1992, Machine Learning.
[35] Christian Bauckhage,et al. Imitation learning at all levels of game-AI , 2004 .
[36] Christian Bauckhage,et al. Learning Human-Like Movement Behavior for Computer Games , 2004 .
[37] Pieter Abbeel,et al. Apprenticeship learning via inverse reinforcement learning , 2004, ICML.
[38] Ales Ude,et al. Programming full-body movements for humanoid robots by observation , 2004, Robotics Auton. Syst..
[39] Y. Demiris,et al. From motor babbling to hierarchical learning by imitation: a robot developmental pathway , 2005 .
[40] José María Valls,et al. Correcting and improving imitation models of humans for Robosoccer agents , 2005, 2005 IEEE Congress on Evolutionary Computation.
[41] D. Feil-Seifer,et al. Defining socially assistive robotics , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..
[42] Jin-Hui Zhu,et al. Obstacle avoidance with multi-objective optimization by PSO in dynamic environment , 2005, 2005 International Conference on Machine Learning and Cybernetics.
[43] Matthew W. Hoffman,et al. Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[44] Jude W. Shavlik,et al. Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another , 2005, ECML.
[45] Pieter Abbeel,et al. An Application of Reinforcement Learning to Aerobatic Helicopter Flight , 2006, NIPS.
[46] Jürgen Schmidhuber,et al. A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[47] Chrystopher L. Nehaniv,et al. Teaching robots by moulding behavior and scaffolding the environment , 2006, HRI '06.
[48] David M. Bradley,et al. Boosting Structured Prediction for Imitation Learning , 2006, NIPS.
[49] Tamim Asfour,et al. Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.
[50] Jürgen Schmidhuber,et al. A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks , 2006 .
[51] Aude Billard,et al. Incremental learning of gestures by imitation in a humanoid robot , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[52] Michael Happold,et al. A Bayesian approach to imitation learning for robot navigation , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[53] Aude Billard,et al. Reinforcement learning for imitating constrained reaching movements , 2007, Adv. Robotics.
[54] Manuela M. Veloso,et al. Confidence-based policy learning from demonstration using Gaussian mixture models , 2007, AAMAS '07.
[55] Aude Billard,et al. What is the Teacher"s Role in Robot Programming by Demonstration? - Toward Benchmarks for Improved Learning , 2007 .
[56] Brett Browning,et al. Learning by demonstration with critique from a human teacher , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[57] Stefan Schaal,et al. Dynamics systems vs. optimal control--a unifying view. , 2007, Progress in brain research.
[58] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[59] Peter Stone,et al. Graph-Based Domain Mapping for Transfer Learning in General Games , 2007, ECML.
[60] Julian Togelius,et al. Towards automatic personalised content creation for racing games , 2007, 2007 IEEE Symposium on Computational Intelligence and Games.
[61] Heni Ben Amor,et al. Towards a Simulator for Imitation Learning with Kinesthetic Bootstrapping , 2008 .
[62] Antonio Bicchi,et al. An atlas of physical human-robot interaction , 2008 .
[63] Anind K. Dey,et al. Maximum Entropy Inverse Reinforcement Learning , 2008, AAAI.
[64] David Silver,et al. High Performance Outdoor Navigation from Overhead Data using Imitation Learning , 2008, Robotics: Science and Systems.
[65] Bart De Schutter,et al. A Comprehensive Survey of Multiagent Reinforcement Learning , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[66] Shang-Jeng Tsai,et al. Optimal UAV flight path planning using skeletonization and Particle Swarm Optimizer , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[67] Aude Billard,et al. A framework integrating statistical and social cues to teach a humanoid robot new skills , 2008, ICRA 2008.
[68] Stefan Schaal,et al. Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.
[69] Betty J. Mohler,et al. Learning perceptual coupling for motor primitives , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[70] Manuela M. Veloso,et al. Teaching collaborative multi-robot tasks through demonstration , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.
[71] Stefan Schaal,et al. 2008 Special Issue: Reinforcement learning of motor skills with policy gradients , 2008 .
[72] Pieter Abbeel,et al. Learning for control from multiple demonstrations , 2008, ICML '08.
[73] Tamim Asfour,et al. Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.
[74] Jan Peters,et al. Learning motor primitives for robotics , 2009, 2009 IEEE International Conference on Robotics and Automation.
[75] Daniele Loiacono,et al. Learning drivers for TORCS through imitation using supervised methods , 2009, 2009 IEEE Symposium on Computational Intelligence and Games.
[76] John Langford,et al. Search-based structured prediction , 2009, Machine Learning.
[77] Araceli Sanchis,et al. Controller for TORCS created by imitation , 2009, 2009 IEEE Symposium on Computational Intelligence and Games.
[78] Brett Browning,et al. A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..
[79] M. Matarić,et al. The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.
[80] Henk Nijmeijer,et al. Robot Programming by Demonstration , 2010, SIMPAR.
[81] Bernard Gorman,et al. Imitation learning through games: theory, implementation and evaluation , 2009 .
[82] Jan Peters,et al. Imitation and Reinforcement Learning , 2010, IEEE Robotics & Automation Magazine.
[83] Araceli Sanchis,et al. A human-like TORCS controller for the Simulated Car Racing Championship , 2010, Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games.
[84] Christoph H. Lampert,et al. Movement templates for learning of hitting and batting , 2010, 2010 IEEE International Conference on Robotics and Automation.
[85] Jan Peters,et al. Noname manuscript No. (will be inserted by the editor) Policy Search for Motor Primitives in Robotics , 2022 .
[86] J. Andrew Bagnell,et al. Efficient Reductions for Imitation Learning , 2010, AISTATS.
[87] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[88] Takashi Minato,et al. Motor Learning for Flexible Joint Humanoid Robots using Physical Human-Robot Interaction , 2010 .
[89] Daobo Wang,et al. UAV path planning method based on ant colony optimization , 2010, 2010 Chinese Control and Decision Conference.
[90] Aude Billard,et al. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models , 2011, IEEE Transactions on Robotics.
[91] Hsien-I Lin,et al. Evaluation of human-robot arm movement imitation , 2011, 2011 8th Asian Control Conference (ASCC).
[92] Bandera Rubio,et al. Vision-based gesture recognition in a robot learning by imitation framework , 2011 .
[93] Stefan Schaal,et al. Learning variable impedance control , 2011, Int. J. Robotics Res..
[94] Geoffrey J. Gordon,et al. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning , 2010, AISTATS.
[95] Stefan Schaal,et al. Skill learning and task outcome prediction for manipulation , 2011, 2011 IEEE International Conference on Robotics and Automation.
[96] Tao Geng,et al. Transferring human grasping synergies to a robot , 2011 .
[97] Julian Togelius,et al. Measuring Intelligence through Games , 2011, ArXiv.
[98] A. M. Alimi,et al. Prototyping a biped robot using an educational robotics kit , 2012, International Conference on Education and e-Learning Innovations.
[99] He He,et al. Imitation Learning by Coaching , 2012, NIPS.
[100] Oliver Kroemer,et al. Learning to select and generalize striking movements in robot table tennis , 2012, AAAI Fall Symposium: Robots Learning Interactively from Human Teachers.
[101] Jürgen Schmidhuber,et al. Multi-column deep neural networks for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[102] Nikolaos G. Tsagarakis,et al. Statistical dynamical systems for skills acquisition in humanoids , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).
[103] Takashi Minato,et al. Physical Human-Robot Interaction: Mutual Learning and Adaptation , 2012, IEEE Robotics & Automation Magazine.
[104] Toyoaki Nishida,et al. Fluid Imitation , 2012, Int. J. Soc. Robotics.
[105] Thomas G. Dietterich,et al. Active Imitation Learning via Reduction to I.I.D. Active Learning , 2012, AAAI Fall Symposium: Robots Learning Interactively from Human Teachers.
[106] P. Hingston. Believable Bots: Can Computers Play Like People? , 2012 .
[107] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[108] Andreas Vlachos,et al. An investigation of imitation learning algorithms for structured prediction , 2012, EWRL.
[109] Philip Hingston,et al. Believable Bots , 2012, Springer Berlin Heidelberg.
[110] Roger Bemelmans,et al. Socially assistive robots in elderly care: a systematic review into effects and effectiveness. , 2012, Journal of the American Medical Directors Association.
[111] Aude Billard,et al. Robot Learning from Failed Demonstrations , 2012, Int. J. Soc. Robotics.
[112] Sajjad Haider,et al. Teaching coordinated strategies to soccer robots via imitation , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).
[113] Carme Torras,et al. A robot learning from demonstration framework to perform force-based manipulation tasks , 2013, Intelligent Service Robotics.
[114] Sergey Levine,et al. Guided Policy Search , 2013, ICML.
[115] Josh C. Bongard,et al. Combining fitness-based search and user modeling in evolutionary robotics , 2013, GECCO '13.
[116] Kenneth O. Stanley,et al. Scalable multiagent learning through indirect encoding of policy geometry , 2013, Evol. Intell..
[117] Carme Torras,et al. Learning Collaborative Impedance-Based Robot Behaviors , 2013, AAAI.
[118] Carlos Balaguer,et al. A humanoid robot standing up through learning from demonstration using a multimodal reward function , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).
[119] Jürgen Schmidhuber,et al. Evolving large-scale neural networks for vision-based reinforcement learning , 2013, GECCO '13.
[120] Jan Peters,et al. Reinforcement learning in robotics: A survey , 2013, Int. J. Robotics Res..
[121] Scott Niekum,et al. Incremental Semantically Grounded Learning from Demonstration , 2013, Robotics: Science and Systems.
[122] Stefan Schaal,et al. From dynamic movement primitives to associative skill memories , 2013, Robotics Auton. Syst..
[123] Joelle Pineau,et al. Learning from Limited Demonstrations , 2013, NIPS.
[124] Jun Nakanishi,et al. Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors , 2013, Neural Computation.
[125] Julian Togelius,et al. Imitating human playing styles in Super Mario Bros , 2013, Entertain. Comput..
[126] Xiaodong Li,et al. Learning a Super Mario controller from examples of human play , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).
[127] Heni Ben Amor,et al. Learning Two-Person Interaction Models for Responsive Synthetic Humanoids , 2014, J. Virtual Real. Broadcast..
[128] Honglak Lee,et al. Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning , 2014, NIPS.
[129] Olivier Sigaud,et al. Learning a repertoire of actions with deep neural networks , 2014, 4th International Conference on Development and Learning and on Epigenetic Robotics.
[130] Matthew E. Taylor,et al. Policy Transfer using Reward Shaping , 2015, AAMAS.
[131] Huan Tan,et al. A Behavior Generation Framework for Robots to Learn from Demonstrations , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.
[132] Tsukasa Ogasawara,et al. Incremental learning of reach-to-grasp behavior: A PSO-based Inverse optimal control approach , 2015, 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR).
[133] Darwin G. Caldwell,et al. Learning optimal controllers in human-robot cooperative transportation tasks with position and force constraints , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[134] Markus Wulfmeier,et al. Maximum Entropy Deep Inverse Reinforcement Learning , 2015, 1507.04888.
[135] William Curran,et al. Using PCA to Efficiently Represent State Spaces , 2015, ArXiv.
[136] Yudong Zhang,et al. A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications , 2015 .
[137] Justin Bayer,et al. Efficient movement representation by embedding Dynamic Movement Primitives in deep autoencoders , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).
[138] Amos J. Storkey,et al. Training Deep Convolutional Neural Networks to Play Go , 2015, ICML.
[139] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[140] Yaochu Jin,et al. A social learning particle swarm optimization algorithm for scalable optimization , 2015, Inf. Sci..
[141] Marc G. Bellemare,et al. The Arcade Learning Environment: An Evaluation Platform for General Agents , 2012, J. Artif. Intell. Res..
[142] Sonia Chernova,et al. Reinforcement Learning from Demonstration through Shaping , 2015, IJCAI.
[143] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[144] Sergey Levine,et al. Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization , 2016, ICML.
[145] Sergey Levine,et al. Learning deep neural network policies with continuous memory states , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[146] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[147] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[148] Rouhollah Rahmatizadeh,et al. Learning Manipulation Trajectories Using Recurrent Neural Networks , 2016, ArXiv.
[149] Mansour A. Karkoub,et al. Humanoid Robot's Visual Imitation of 3-D Motion of a Human Subject Using Neural-Network-Based Inverse Kinematics , 2016, IEEE Systems Journal.
[150] Yisong Yue,et al. Smooth Imitation Learning for Online Sequence Prediction , 2016, ICML.
[151] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[152] Charlie C. L. Wang,et al. Motion Imitation Based on Sparsely Sampled Correspondence , 2017, J. Comput. Inf. Sci. Eng..
[153] Stefan Schaal,et al. Learning from Demonstration , 1996, NIPS.