Intrinsic Motivation Systems for Autonomous Mental Development
暂无分享,去创建一个
Pierre-Yves Oudeyer | Frédéric Kaplan | Verena V. Hafner | Pierre-Yves Oudeyer | F. Kaplan | V. Hafner | P. Oudeyer
[1] R. Yerkes. Mental Development in the Child and the Race , 1907, The American Naturalist.
[2] J. Piaget. Play, dreams and imitation in childhood , 1951 .
[3] R. W. White. Motivation reconsidered: the concept of competence. , 1959, Psychological review.
[4] Peter Secretan. Learning , 1965, Mental Health.
[5] Marvin Minsky,et al. A framework for representing knowledge , 1974 .
[6] Marvin Minsky,et al. A framework for representing knowledge" in the psychology of computer vision , 1975 .
[7] P. L. Adams. THE ORIGINS OF INTELLIGENCE IN CHILDREN , 1976 .
[8] Roger C. Schank,et al. Scripts, plans, goals and understanding: an inquiry into human knowledge structures , 1978 .
[9] L. Vygotsky. Mind in Society: The Development of Higher Psychological Processes: Harvard University Press , 1978 .
[10] J. Gibson. The Ecological Approach to Visual Perception , 1979 .
[11] Edward L. Deci,et al. Intrinsic Motivation and Self-Determination in Human Behavior , 1975, Perspectives in Social Psychology.
[12] K. Miller,et al. Intrinsic Motivation and Self-Determination in Human Behavior , 1975, Perspectives in Social Psychology.
[13] M. Csíkszentmihályi. Flow: The Psychology of Optimal Experience , 1990 .
[14] Jürgen Schmidhuber,et al. Curious model-building control systems , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.
[15] David J. C. MacKay,et al. Information-Based Objective Functions for Active Data Selection , 1992, Neural Computation.
[16] T. Watkin,et al. Selecting examples for perceptrons , 1992 .
[17] Mark Plutowski,et al. Selecting concise training sets from clean data , 1993, IEEE Trans. Neural Networks.
[18] J. Elman. Learning and development in neural networks: the importance of starting small , 1993, Cognition.
[19] David A. Cohn,et al. Active Learning with Statistical Models , 1996, NIPS.
[20] Gerhard Paass,et al. Bayesian Query Construction for Neural Network Models , 1994, NIPS.
[21] C. Moore,et al. Social Understanding at the End of the First Year of Life , 1994 .
[22] Michael A. Arbib,et al. The handbook of brain theory and neural networks , 1995, A Bradford book.
[23] D. Lewkowicz,et al. A dynamic systems approach to the development of cognition and action. , 2007, Journal of cognitive neuroscience.
[24] M. Csíkszentmihályi. Creativity: Flow and the Psychology of Discovery and Invention , 1996 .
[25] Anthony V. Robins,et al. Transfer in Cognition , 1996, Connect. Sci..
[26] Lorien Y. Pratt,et al. A Survey of Transfer Between Connectionist Networks , 1996, Connect. Sci..
[27] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[28] Frank Dignum,et al. Intentional Agents and Goal Formation , 1997, ATAL.
[29] Kenneth W. Bauer,et al. Selecting Optimal Experiments for Multiple Output Multilayer Perceptrons , 1997, Neural Computation.
[30] Jean-Arcady Meyer,et al. Learning to Perceive the World as Articulated: An Approach for Hierarchical Learning in Sensory-Motor Systems , 1998 .
[31] Sebastian Thrun,et al. Exploration in active learning , 1998 .
[32] Lorien Y. Pratt,et al. A Survey of Connectionist Network Reuse Through Transfer , 1998, Learning to Learn.
[33] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[34] G. Lakoff,et al. Philosophy in the flesh : the embodied mind and its challenge to Western thought , 1999 .
[35] Stefano Nolfi,et al. Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems , 1998, Neural Networks.
[36] M. Hasenjäger,et al. Active Learning in Self-Organizing Maps , 1999 .
[37] Stefano Nolfi,et al. Extracting Regularities in Space and Time Through a Cascade of Prediction Networks: The Case of a Mobile Robot Navigating in a Structured Environment , 1999, Connect. Sci..
[38] J. Michael Herrmann,et al. Learning predictive representations , 2000, Neurocomputing.
[39] Jun Rekimoto,et al. CyberCode: designing augmented reality environments with visual tags , 2000, DARE '00.
[40] J. Horvitz. Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events , 2000, Neuroscience.
[41] Andrew McCallum,et al. Toward Optimal Active Learning through Sampling Estimation of Error Reduction , 2001, ICML.
[42] James L. McClelland,et al. Autonomous Mental Development by Robots and Animals , 2001, Science.
[43] Samy Bengio,et al. SVMTorch: Support Vector Machines for Large-Scale Regression Problems , 2001, J. Mach. Learn. Res..
[44] D. Gentner,et al. The analogical mind : perspectives from cognitive science , 2001 .
[45] Kunihiko Kaneko,et al. Complex Systems: Chaos and Beyond , 2001 .
[46] W. Prinz,et al. Ego function of early imitation , 2002 .
[47] M. Hasenjäger,et al. Active learning in neural networks , 2002 .
[48] Mitsuo Kawato,et al. Multiple Model-Based Reinforcement Learning , 2002, Neural Computation.
[49] Xiao Huang,et al. Novelty and Reinforcement Learning in the Value System of Developmental Robots , 2002 .
[50] J. Grady. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought , 2002 .
[51] P. Dayan,et al. Reward, Motivation, and Reinforcement Learning , 2002, Neuron.
[52] Juyang Weng,et al. A theory for mentally developing robots , 2002, Proceedings 2nd International Conference on Development and Learning. ICDL 2002.
[53] Andreas Zell,et al. Different criteria for active learning in neural networks: a comparative study , 2002, ESANN.
[54] Joachim Denzler,et al. Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[55] W. Prinz,et al. The imitative mind : development, evolution, and brain bases , 2002 .
[56] Peter Dayan,et al. Dopamine: generalization and bonuses , 2002, Neural Networks.
[57] Pierre-Yves Oudeyer,et al. Motivational principles for visual know-how development , 2003 .
[58] Randall D. Beer,et al. The Dynamics of Active Categorical Perception in an Evolved Model Agent , 2003, Adapt. Behav..
[59] Luc Steels,et al. The Autotelic Principle , 2003, Embodied Artificial Intelligence.
[60] Olaf Sporns,et al. Information-Theoretical Aspects of Embodied Artificial Intelligence , 2003, Embodied Artificial Intelligence.
[61] Giulio Sandini,et al. Developmental robotics: a survey , 2003, Connect. Sci..
[62] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[63] Jean-Christophe Baillie. URBI: A UNIVERSAL LANGUAGE FOR ROBOTIC CONTROL , 2004 .
[64] Minoru Asada,et al. Purposive behavior acquisition for a real robot by vision-based reinforcement learning , 1995, Machine Learning.
[65] Jun Tani,et al. Self-organization of distributedly represented multiple behavior schemata in a mirror system: reviews of robot experiments using RNNPB , 2004, Neural Networks.
[66] Stefan Schaal,et al. Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning , 2002, Applied Intelligence.
[67] Juyang Weng,et al. Developmental Robotics: Theory and Experiments , 2004, Int. J. Humanoid Robotics.
[68] Nuttapong Chentanez,et al. Intrinsically Motivated Learning of Hierarchical Collections of Skills , 2004 .
[69] O. Michel. WebotsTM: Professional Mobile Robot Simulation , 2004, ArXiv.
[70] Olivier Michel,et al. Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004 .
[71] David A. Cohn,et al. Improving generalization with active learning , 1994, Machine Learning.
[72] Douglas S. Blank,et al. An Emergent Framework For Self-Motivation In Developmental Robotics , 2004 .
[73] Jean-Christophe Baillie,et al. URBI: towards a universal robotic low-level programming language , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[74] M. Cole,et al. Mind in Society , 2005 .
[75] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[76] Minoru Asada,et al. Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning , 2005, Machine Learning.
[77] M. Tomasello,et al. Understanding and sharing intentions: The origins of cultural cognition , 2005, Behavioral and Brain Sciences.
[78] F. Kaplan,et al. The challenges of joint attention , 2006 .
[79] Pierre-Yves Oudeyer,et al. The progress drive hypothesis: an interpretation of early imitation , 2007 .