Reinforcement Learning Approaches in Social Robotics
暂无分享,去创建一个
[1] Ruben Villegas,et al. Learning Latent Dynamics for Planning from Pixels , 2018, ICML.
[2] David L. Roberts,et al. Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning , 2015, Autonomous Agents and Multi-Agent Systems.
[3] Kaoru Hirota,et al. Adapting Multi-Robot Behavior to Communication Atmosphere in Humans-Robots Interaction Using Fuzzy Production Rule Based Friend-Q Learning , 2013, J. Adv. Comput. Intell. Intell. Informatics.
[4] Eduardo F. Morales,et al. An Introduction to Reinforcement Learning , 2011 .
[5] Gerhard Sagerer,et al. Understanding Social Robots , 2009, 2009 Second International Conferences on Advances in Computer-Human Interactions.
[6] Marzie Zarinbal,et al. A New Social Robot for Interactive Query-Based Summarization: Scientific Document Summarization , 2019, ICR.
[7] Elisabeth André,et al. Adaptive linguistic style for an assistive robotic health companion based on explicit human feedback , 2019, PETRA.
[8] Brian R. Duffy,et al. Anthropomorphism and the social robot , 2003, Robotics Auton. Syst..
[9] C. Breazeal,et al. Experiments in socially guided exploration: lessons learned in building robots that learn with and without human teachers , 2008, Connect. Sci..
[10] Richard S. Sutton,et al. Learning and Sequential Decision Making , 1989 .
[11] Andrea Lockerd Thomaz,et al. Tutelage and socially guided robot learning , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).
[12] Sridhar Mahadevan,et al. Average reward reinforcement learning: Foundations, algorithms, and empirical results , 2004, Machine Learning.
[13] Dimitrios Tzovaras,et al. A POMDP Design Framework for Decision Making in Assistive Robots , 2017, HCI.
[14] Yuichiro Yoshikawa,et al. Robot gains social intelligence through multimodal deep reinforcement learning , 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).
[15] E. Deci,et al. Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. , 2000, Contemporary educational psychology.
[16] Danica Kragic,et al. A sensorimotor reinforcement learning framework for physical Human-Robot Interaction , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[17] Oliver Lemon,et al. Hybrid chat and task dialogue for more engaging HRI using reinforcement learning , 2017, 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
[18] Lili Liu,et al. Interactive robots as social partner for communication care , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[19] Sonia Chernova,et al. Effect of human guidance and state space size on Interactive Reinforcement Learning , 2011, 2011 RO-MAN.
[20] J. Lerner,et al. Emotion and decision making. , 2015, Annual review of psychology.
[21] Pierre-Yves Oudeyer,et al. How can we define intrinsic motivation , 2008 .
[22] Anton Schwartz,et al. A Reinforcement Learning Method for Maximizing Undiscounted Rewards , 1993, ICML.
[23] Roseli A. Francelin Romero,et al. Relational reinforcement learning applied to shared attention , 2009, 2009 International Joint Conference on Neural Networks.
[24] Andreas Ernst,et al. Face Detection with the Sophisticated High-speed Object Recognition Engine (SHORE) , 2011 .
[25] W. Cannon. The Wisdom of the Body , 1932 .
[26] Kenji Suzuki,et al. A lesson from subjective computing: autonomous self-referentiality and social interaction as conditions for subjectivity , 2013 .
[27] Anil A. Bharath,et al. Deep Reinforcement Learning: A Brief Survey , 2017, IEEE Signal Processing Magazine.
[28] Jan Peters,et al. A Survey on Policy Search for Robotics , 2013, Found. Trends Robotics.
[29] Hongliang Ren,et al. Deep Reinforcement Learning for Soft, Flexible Robots: Brief Review with Impending Challenges , 2019, Robotics.
[30] C. Bartneck,et al. A design-centred framework for social human-robot interaction , 2004, RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication (IEEE Catalog No.04TH8759).
[31] Goldie Nejat,et al. Can I be of assistance? The intelligence behind an assistive robot , 2008, 2008 IEEE International Conference on Robotics and Automation.
[32] Eric Wiewiora,et al. Reward Shaping , 2017, Encyclopedia of Machine Learning and Data Mining.
[33] Yaser Sheikh,et al. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Alex Mihailidis,et al. Learning and Personalizing Socially Assistive Robot Behaviors to Aid with Activities of Daily Living , 2018, ACM Transactions on Human-Robot Interaction.
[35] Nikolaos Mavridis,et al. A review of verbal and non-verbal human-robot interactive communication , 2014, Robotics Auton. Syst..
[36] Roseli A. Francelin Romero,et al. Modelling Shared Attention Through Relational Reinforcement Learning , 2012, J. Intell. Robotic Syst..
[37] María Malfaz,et al. A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User , 2018, Sensors.
[38] K. Berridge. Motivation concepts in behavioral neuroscience , 2004, Physiology & Behavior.
[39] Ronen I. Brafman,et al. R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning , 2001, J. Mach. Learn. Res..
[40] Yuichiro Yoshikawa,et al. Show, attend and interact: Perceivable human-robot social interaction through neural attention Q-network , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[41] Jinhua She,et al. Information-Driven Multirobot Behavior Adaptation to Emotional Intention in Human–Robot Interaction , 2018, IEEE Transactions on Cognitive and Developmental Systems.
[42] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[43] Jorge Dias,et al. αPOMDP: POMDP-based user-adaptive decision-making for social robots , 2019, Pattern Recognit. Lett..
[44] Mahesan Niranjan,et al. On-line Q-learning using connectionist systems , 1994 .
[45] Olivier Sigaud,et al. Policy Search in Continuous Action Domains: an Overview , 2018, Neural Networks.
[46] Goldie Nejat,et al. Minimizing task-induced stress in cognitively stimulating activities using an intelligent socially assistive robot , 2011, 2011 RO-MAN.
[47] Andrea Lockerd Thomaz,et al. Teachable robots: Understanding human teaching behavior to build more effective robot learners , 2008, Artif. Intell..
[48] Elisabeth André,et al. Drink-O-Mender: An Adaptive Robotic Drink Adviser , 2018, MHFI@ICMI.
[49] Andrea L. Thomaz,et al. Socially guided machine learning , 2006 .
[50] Pierre-Yves Oudeyer,et al. What is Intrinsic Motivation? A Typology of Computational Approaches , 2007, Frontiers Neurorobotics.
[51] Javier Ruiz-del-Solar,et al. An Interactive Framework for Learning Continuous Actions Policies Based on Corrective Feedback , 2018, Journal of Intelligent & Robotic Systems.
[52] Cynthia Breazeal,et al. Toward sociable robots , 2003, Robotics Auton. Syst..
[53] Peter Stone,et al. Interactively shaping agents via human reinforcement: the TAMER framework , 2009, K-CAP '09.
[54] R Bellman,et al. On the Theory of Dynamic Programming. , 1952, Proceedings of the National Academy of Sciences of the United States of America.
[55] Cynthia Breazeal,et al. A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education , 2019, AAAI.
[56] Min Wu,et al. Emotion Regulation Based on Multi-objective Weighted Reinforcement Learning for Human-robot Interaction , 2019, 2019 12th Asian Control Conference (ASCC).
[57] Cynthia Breazeal,et al. Affective Personalization of a Social Robot Tutor for Children's Second Language Skills , 2016, AAAI.
[58] Thomas G. Dietterich. Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition , 1999, J. Artif. Intell. Res..
[59] Li-Chen Fu,et al. A companion robot for daily care of elders based on homeostasis , 2017, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).
[60] Fillia Makedon,et al. Adaptive Robot Assisted Therapy Using Interactive Reinforcement Learning , 2016, ICSR.
[61] Fillia Makedon,et al. Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training , 2018 .
[62] Abhijit Gosavi,et al. Boundedness of iterates in Q-Learning , 2006, Syst. Control. Lett..
[63] Patrick M. Pilarski,et al. Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction , 2011, AAMAS.
[64] María Malfaz,et al. A Biologically Inspired Architecture for an Autonomous and Social Robot , 2011, IEEE Transactions on Autonomous Mental Development.
[65] Bo He,et al. Human-Centered Reinforcement Learning: A Survey , 2019, IEEE Transactions on Human-Machine Systems.
[66] Darwin G. Caldwell,et al. Reinforcement Learning in Robotics: Applications and Real-World Challenges , 2013, Robotics.
[67] Peter Stone,et al. Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance , 2015, Artif. Intell..
[68] Heriberto Cuayáhuitl,et al. A Data-Efficient Deep Learning Approach for Deployable Multimodal Social Robots , 2019, Neurocomputing.
[69] C. Breazeal. Role of expressive behaviour for robots that learn from people , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.
[70] Yuan Gao,et al. When Robot Personalisation Does Not Help: Insights from a Robot-Supported Learning Study , 2018, 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
[71] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[72] Radu Horaud,et al. Neural Network Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction , 2017, Pattern Recognit. Lett..
[73] Marcelo H. Ang,et al. A Survey on Perception Methods for Human–Robot Interaction in Social Robots , 2013, International Journal of Social Robotics.
[74] Takayuki Kanda,et al. Robot Behavior Adaptation for Human-Robot Interaction based on Policy Gradient Reinforcement Learning , 2005 .
[75] Huasen Wu,et al. Double Thompson Sampling for Dueling Bandits , 2016, NIPS.
[76] Hongming Zhang,et al. Taxonomy of Reinforcement Learning Algorithms , 2020 .
[77] Mehdi Khamassi,et al. Robot Fast Adaptation to Changes in Human Engagement During Simulated Dynamic Social Interaction With Active Exploration in Parameterized Reinforcement Learning , 2018, IEEE Transactions on Cognitive and Developmental Systems.
[78] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[79] Oliver Lemon,et al. Machine Learning for Social Multiparty Human--Robot Interaction , 2014, TIIS.
[80] Peter Stone,et al. Deep Recurrent Q-Learning for Partially Observable MDPs , 2015, AAAI Fall Symposia.
[81] María Malfaz,et al. Learning the Selection of Actions for an Autonomous Social Robot by Reinforcement Learning Based on Motivations , 2011, Int. J. Soc. Robotics.
[82] María Malfaz,et al. An Autonomous Social Robot in Fear , 2013, IEEE Transactions on Autonomous Mental Development.
[83] Shimon Whiteson,et al. A Survey of Multi-Objective Sequential Decision-Making , 2013, J. Artif. Intell. Res..
[84] Andrea Lockerd Thomaz,et al. Reinforcement Learning with Human Teachers: Understanding How People Want to Teach Robots , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.
[85] Ben J. A. Kröse,et al. Learning from delayed rewards , 1995, Robotics Auton. Syst..
[86] Andrea Lockerd Thomaz,et al. Asymmetric Interpretations of Positive and Negative Human Feedback for a Social Learning Agent , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.
[87] Brian Scassellati,et al. Personalized Robot Tutoring Using the Assistive Tutor POMDP (AT-POMDP) , 2019, AAAI.
[88] Nak Young Chong,et al. Learning Proxemics for Personalized Human–Robot Social Interaction , 2020, Int. J. Soc. Robotics.
[89] Takayuki Kanda,et al. Adapting Robot Behavior for Human--Robot Interaction , 2008, IEEE Transactions on Robotics.
[90] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[91] Franz Kummert,et al. Exploring embodiment and dueling bandit learning for preference adaptation in human-robot interaction , 2017, 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
[92] María Malfaz,et al. LEARNING BEHAVIORS BY AN AUTONOMOUS SOCIAL ROBOT WITH MOTIVATIONS , 2014, Cybern. Syst..
[93] Fillia Makedon,et al. Enhanced therapeutic interactivity using social robot Zeno , 2011, PETRA '11.
[94] Radu Horaud,et al. Deep Reinforcement Learning for Audio-Visual Gaze Control , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[95] Tony Belpaeme,et al. Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction , 2015, PloS one.
[96] Ana Paiva,et al. Modelling Empathy in Social Robotic Companions , 2011, UMAP Workshops.
[97] Kenji Suzuki,et al. An Approach to Subjective Computing: A Robot That Learns From Interaction With Humans , 2014, IEEE Transactions on Autonomous Mental Development.
[98] Cynthia Breazeal,et al. Training a Robot via Human Feedback: A Case Study , 2013, ICSR.
[99] Javier García,et al. A comprehensive survey on safe reinforcement learning , 2015, J. Mach. Learn. Res..
[100] Tobias Baur,et al. Adapting a Robot's linguistic style based on socially-aware reinforcement learning , 2017, 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).
[101] Daniel McDuff,et al. AFFDEX SDK: A Cross-Platform Real-Time Multi-Face Expression Recognition Toolkit , 2016, CHI Extended Abstracts.
[102] S. Kopp,et al. Towards Adaptive Social Behavior Generation for Assistive Robots Using Reinforcement Learning , 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.
[103] Goldie Nejat,et al. A learning-based control architecture for an assistive robot providing social engagement during cognitively stimulating activities , 2011, 2011 IEEE International Conference on Robotics and Automation.
[104] Gabriel Dulac-Arnold,et al. Challenges of Real-World Reinforcement Learning , 2019, ArXiv.
[105] Peter Stone,et al. Reinforcement learning from simultaneous human and MDP reward , 2012, AAMAS.
[106] Nuttapong Chentanez,et al. Intrinsically Motivated Reinforcement Learning , 2004, NIPS.
[107] James L. Crowley,et al. Learning polite behavior with situation models , 2008, 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[108] Chu Kiong Loo,et al. Extensive assessment and evaluation methodologies on assistive social robots for modelling human-robot interaction - A review , 2015, Inf. Sci..
[109] Andrea Lockerd Thomaz,et al. Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance , 2006, AAAI.
[110] Peng Liu,et al. Guided goal generation for hindsight multi-goal reinforcement learning , 2019, Neurocomputing.
[111] Catholijn M. Jonker,et al. Emotion in reinforcement learning agents and robots: a survey , 2017, Machine Learning.
[112] Peter Stone,et al. A social reinforcement learning agent , 2001, AGENTS '01.
[113] Li-Chen Fu,et al. Active Learning on Service Providing Model: Adjustment of Robot Behaviors Through Human Feedback , 2018, IEEE Transactions on Cognitive and Developmental Systems.
[114] Adriana Tapus,et al. User—robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy , 2008, Intell. Serv. Robotics.
[115] Stefan Wermter,et al. Learning Empathy-Driven Emotion Expressions using Affective Modulations , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).
[116] Li-Chen Fu,et al. Interactive Reinforcement Learning based Assistive Robot for the Emotional Support of Children , 2018, 2018 18th International Conference on Control, Automation and Systems (ICCAS).
[117] Tobias Baur,et al. The social signal interpretation (SSI) framework: multimodal signal processing and recognition in real-time , 2013, ACM Multimedia.
[118] Goldie Nejat,et al. Social Intelligence for a Robot Engaging People in Cognitive Training Activities , 2012 .
[119] Guy Hoffman,et al. Computational Human-Robot Interaction , 2016, Found. Trends Robotics.
[120] Leopoldina Fortunati,et al. How many facets does a "social robot" have? A review of scientific and popular definitions online , 2019, Inf. Technol. People.
[121] María Malfaz,et al. Bioinspired decision-making for a socially interactive robot , 2019, Cognitive Systems Research.
[122] Thomas E. Joiner,et al. A measure of positive and negative affect for children: Scale development and preliminary validation. , 1999 .
[123] Sonia Chernova,et al. A Practical Comparison of Three Robot Learning from Demonstration Algorithm , 2012, Int. J. Soc. Robotics.
[124] Jan Peters,et al. Reinforcement learning in robotics: A survey , 2013, Int. J. Robotics Res..
[125] Albrecht Schmidt,et al. Implicit human computer interaction through context , 2000, Personal Technologies.
[126] Illah R. Nourbakhsh,et al. A survey of socially interactive robots , 2003, Robotics Auton. Syst..
[127] Elisabeth André,et al. How to Shape the Humor of a Robot - Social Behavior Adaptation Based on Reinforcement Learning , 2018, ICMI.
[128] M. Kubát. An Introduction to Machine Learning , 2017, Springer International Publishing.
[129] C. Watkins. Learning from delayed rewards , 1989 .
[130] Sébastien Bubeck,et al. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , 2012, Found. Trends Mach. Learn..
[131] Sheikh Iqbal Ahamed,et al. Applying affective feedback to reinforcement learning in ZOEI, a comic humanoid robot , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.
[132] Li-Chen Fu,et al. Personalizing robot behavior for interruption in social human-robot interaction , 2014, 2014 IEEE International Workshop on Advanced Robotics and its Social Impacts.
[133] Yuichiro Yoshikawa,et al. Intrinsically motivated reinforcement learning for human-robot interaction in the real-world , 2018, Neural Networks.
[134] Camelia-Mihaela Pintea,et al. Towards interactive Machine Learning (iML): Applying Ant Colony Algorithms to Solve the Traveling Salesman Problem with the Human-in-the-Loop Approach , 2016, CD-ARES.
[135] Lina Yao,et al. Intent Recognition in Smart Living Through Deep Recurrent Neural Networks , 2017, ICONIP.