Robot Weightlifting By Direct Policy Search
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[1] N. A. Bernshteĭn. The co-ordination and regulation of movements , 1967 .
[2] Peter H. Greene,et al. Problems of Organization of Motor Systems , 1972 .
[3] D. Winfield,et al. Optimization: Theory and practice , 1972 .
[4] Nils J. Nilsson,et al. Artificial Intelligence , 1974, IFIP Congress.
[5] R. Schmidt. A schema theory of discrete motor skill learning. , 1975 .
[6] David E. Orin,et al. Efficient Dynamic Computer Simulation of Robotic Mechanisms , 1982 .
[7] P. H. Greene,et al. Why is it easy to control your arms ? , 1982, Journal of motor behavior.
[8] A. G. Feldman. Once More on the Equilibrium-Point Hypothesis (λ Model) for Motor Control , 1986 .
[9] S. Shankar Sastry,et al. Adaptive Control of Mechanical Manipulators , 1987 .
[10] Russell W. Anderson. Biased Random-Walk Learning: A Neurobiological Correlate to Trial-and-Error , 1993, adap-org/9305002.
[11] Andrew W. Moore,et al. The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces , 2004, Machine Learning.
[12] Peter L. Rogers,et al. Measurement and Control , 1993 .
[13] G. J. van Ingen Schenau,et al. The control of multi-joint movements relies on detailed internal representations , 1995 .
[14] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[15] John N. Tsitsiklis,et al. Analysis of Temporal-Diffference Learning with Function Approximation , 1996, NIPS.
[16] Jun Morimoto,et al. Conference on Intelligent Robots and Systems Reinforcement Le,arning of Dynamic Motor Sequence: Learning to Stand Up , 2022 .
[17] Andrew W. Moore,et al. Gradient Descent for General Reinforcement Learning , 1998, NIPS.
[18] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[19] James E. Bobrow,et al. Weight lifting motion planning for a Puma 762 robot , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).
[20] John J. Grefenstette,et al. Evolutionary Algorithms for Reinforcement Learning , 1999, J. Artif. Intell. Res..
[21] Yishay Mansour,et al. Policy Gradient Methods for Reinforcement Learning with Function Approximation , 1999, NIPS.
[22] Stefan Schaal,et al. Is imitation learning the route to humanoid robots? , 1999, Trends in Cognitive Sciences.
[23] Charles W. Anderson,et al. Approximating a Policy Can be Easier Than Approximating a Value Function , 2000 .
[24] Craig Boutilier,et al. Stochastic dynamic programming with factored representations , 2000, Artif. Intell..
[25] Peter L. Bartlett,et al. Reinforcement Learning in POMDP's via Direct Gradient Ascent , 2000, ICML.
[26] S. Grossberg,et al. Psychological Review , 2003 .