Hierarchical motor control in mammals and machines
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[1] K. Lashley. Basic neural mechanisms in behavior. , 1930 .
[2] E. Culler,et al. Conditioned behavior in a decorticate dog. , 1934 .
[3] R. McK.. Certain Aspects of the Behavior of Decorticate Cats , 1938 .
[4] William Rowan,et al. The Study of Instinct , 1953 .
[5] H. Evans. The Study of Instinct , 1952 .
[6] Marvin Minsky,et al. Steps toward Artificial Intelligence , 1995, Proceedings of the IRE.
[7] R. Bellman. Dynamic programming. , 1957, Science.
[8] M. Wayner. Motor control functions of the lateral hypothalamus and adjunctive behavior. , 1970, Physiology & behavior.
[9] CHANNELING OF RESPONSES ELICITED BY HYPOTHALAMIC STIMULATION , 1972 .
[10] R. Wise. Lateral hypothalamic electrical stimulation: does it make animals 'hungry'? , 1974, Brain research.
[11] J. Tanji,et al. Anticipatory activity of motor cortex neurons in relation to direction of an intended movement. , 1976, Journal of neurophysiology.
[12] M. Raibert. Motor Control and Learning by the State Space Model , 1977 .
[13] Douglas L. Jones,et al. From motivation to action: Functional interface between the limbic system and the motor system , 1980, Progress in Neurobiology.
[14] S. Grillner. Neurobiological bases of rhythmic motor acts in vertebrates. , 1985, Science.
[15] T. Flash,et al. The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[16] I. Whishaw,et al. The mating movements of male decorticate rats: Evidence for subcortically generated movements by the male but regulation of approaches by the female , 1985, Behavioural Brain Research.
[17] Rodney A. Brooks,et al. A Robust Layered Control Syste For A Mobile Robot , 2022 .
[18] Dean Pomerleau,et al. ALVINN, an autonomous land vehicle in a neural network , 2015 .
[19] F A Mussa-Ivaldi,et al. Computations underlying the execution of movement: a biological perspective. , 1991, Science.
[20] Geoffrey E. Hinton,et al. Feudal Reinforcement Learning , 1992, NIPS.
[21] M. Udo,et al. A new learning paradigm: adaptive changes in interlimb coordination during perturbed locomotion in decerebrate cats , 1993, Neuroscience Research.
[22] 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.
[23] Richard S. Sutton,et al. A Menu of Designs for Reinforcement Learning Over Time , 1995 .
[24] Örjan Ekeberg,et al. The Neural Control of Fish Swimming Studied Through Numerical Simulations , 1995, Adapt. Behav..
[25] Ivan Bratko,et al. Behavioural Cloning: Phenomena, Results and Problems , 1995 .
[26] Joel L. Davis,et al. In : Models of Information Processing in the Basal Ganglia , 2008 .
[27] P. Whelan. CONTROL OF LOCOMOTION IN THE DECEREBRATE CAT , 1996, Progress in Neurobiology.
[28] N. A. Bernstein. Dexterity and Its Development , 1996 .
[29] Daniel M. Wolpert,et al. Forward Models for Physiological Motor Control , 1996, Neural Networks.
[30] Michael I. Jordan. Chapter 2 Computational aspects of motor control and motor learning , 1996 .
[31] Richard S. J. Frackowiak,et al. Anatomy of motor learning. II. Subcortical structures and learning by trial and error. , 1997, Journal of neurophysiology.
[32] Geoffrey E. Hinton,et al. NeuroAnimator: fast neural network emulation and control of physics-based models , 1998, SIGGRAPH.
[33] I. Whishaw,et al. Paw and limb use in skilled and spontaneous reaching after pyramidal tract, red nucleus and combined lesions in the rat: behavioral and anatomical dissociations , 1998, Behavioural Brain Research.
[34] Mitsuo Kawato,et al. Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.
[35] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[36] Peter Redgrave,et al. Layered Control Architectures in Robots and Vertebrates , 1999, Adapt. Behav..
[37] D. Rose. Progress in Motor Control: Bernstein's Traditions in Movement Studies, Volume 1 , 1999 .
[38] M. Tomasello. The Cultural Origins of Human Cognition , 2000 .
[39] L. Swanson. Cerebral hemisphere regulation of motivated behavior 1 1 Published on the World Wide Web on 2 November 2000. , 2000, Brain Research.
[40] Zoubin Ghahramani,et al. Computational principles of movement neuroscience , 2000, Nature Neuroscience.
[41] E. Bizzi,et al. New perspectives on spinal motor systems , 2000, Nature Reviews Neuroscience.
[42] E. Marder,et al. Central pattern generators and the control of rhythmic movements , 2001, Current Biology.
[43] G. Rizzolatti,et al. Neurophysiological mechanisms underlying the understanding and imitation of action , 2001, Nature Reviews Neuroscience.
[44] Petros Faloutsos,et al. Composable controllers for physics-based character animation , 2001, SIGGRAPH.
[45] Michael I. Jordan,et al. Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.
[46] M. Graziano,et al. Complex Movements Evoked by Microstimulation of Precentral Cortex , 2002, Neuron.
[47] Sridhar Mahadevan,et al. Recent Advances in Hierarchical Reinforcement Learning , 2003, Discret. Event Dyn. Syst..
[48] Zoubin Ghahramani,et al. Unsupervised learning of sensory-motor primitives , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).
[49] V. Dietz. Spinal cord pattern generators for locomotion , 2003, Clinical Neurophysiology.
[50] Miomir Vukobratovic,et al. Zero-Moment Point - Thirty Five Years of its Life , 2004, Int. J. Humanoid Robotics.
[51] S. Grillner,et al. On the central generation of locomotion in the low spinal cat , 1979, Experimental Brain Research.
[52] E. Todorov. Optimality principles in sensorimotor control , 2004, Nature Neuroscience.
[53] Emanuel Todorov,et al. From task parameters to motor synergies: A hierarchical framework for approximately optimal control of redundant manipulators , 2005 .
[54] Emanuel Todorov,et al. From task parameters to motor synergies: A hierarchical framework for approximately optimal control of redundant manipulators , 2005, J. Field Robotics.
[55] Scott L. Delp,et al. A Model of the Upper Extremity for Simulating Musculoskeletal Surgery and Analyzing Neuromuscular Control , 2005, Annals of Biomedical Engineering.
[56] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[57] Aaron S. Andalman,et al. Vocal Experimentation in the Juvenile Songbird Requires a Basal Ganglia Circuit , 2005, PLoS biology.
[58] K. Pearson,et al. Computer simulation of stepping in the hind legs of the cat: an examination of mechanisms regulating the stance-to-swing transition. , 2005, Journal of neurophysiology.
[59] Byron M. Yu,et al. Neural Variability in Premotor Cortex Provides a Signature of Motor Preparation , 2006, The Journal of Neuroscience.
[60] Rajesh P. N. Rao,et al. Bayesian brain : probabilistic approaches to neural coding , 2006 .
[61] Emanuel Todorov,et al. Optimal Control Theory , 2006 .
[62] George K York,et al. An introduction to the life and work of John Hughlings Jackson with a catalogue raisonné of his writings. , 2006, Medical history. Supplement.
[63] J. Jackson. An Introduction to the Life and Work of John Hughlings Jackson , 2006, Medical History.
[64] A. Ijspeert,et al. From Swimming to Walking with a Salamander Robot Driven by a Spinal Cord Model , 2007, Science.
[65] G. Csibra,et al. 'Obsessed with goals': functions and mechanisms of teleological interpretation of actions in humans. , 2007, Acta psychologica.
[66] M. V. D. Panne,et al. SIMBICON: simple biped locomotion control , 2007, SIGGRAPH 2007.
[67] Auke Jan Ijspeert,et al. Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.
[68] S. Grillner,et al. Neural bases of goal-directed locomotion in vertebrates—An overview , 2008, Brain Research Reviews.
[69] David Badre,et al. Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes , 2008, Trends in Cognitive Sciences.
[70] Michale S Fee,et al. A Specialized Forebrain Circuit for Vocal Babbling in the Juvenile Songbird , 2008, Science.
[71] R. Lemon. Descending pathways in motor control. , 2008, Annual review of neuroscience.
[72] Michael I. Jordan. Computational aspects of motor control and motor learning , 2008 .
[73] M. Tomasello. Origins of human communication , 2008 .
[74] Scott L. Delp,et al. A Model of the Lower Limb for Analysis of Human Movement , 2010, Annals of Biomedical Engineering.
[75] M. Botvinick,et al. Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective , 2009, Cognition.
[76] Hillel J. Chiel,et al. The Brain in Its Body: Motor Control and Sensing in a Biomechanical Context , 2009, The Journal of Neuroscience.
[77] J. Andrew Bagnell,et al. Efficient Reductions for Imitation Learning , 2010, AISTATS.
[78] Aaron Hertzmann,et al. Robust physics-based locomotion using low-dimensional planning , 2010, SIGGRAPH 2010.
[79] Benjamin O. Turner,et al. Cortical and basal ganglia contributions to habit learning and automaticity , 2010, Trends in Cognitive Sciences.
[80] R. Ivry,et al. The coordination of movement: optimal feedback control and beyond , 2010, Trends in Cognitive Sciences.
[81] A. Karpathy,et al. Locomotion skills for simulated quadrupeds , 2011, SIGGRAPH 2011.
[82] A. d’Avella,et al. Locomotor Primitives in Newborn Babies and Their Development , 2011, Science.
[83] G. Csibra,et al. Natural pedagogy as evolutionary adaptation , 2011, Philosophical Transactions of the Royal Society B: Biological Sciences.
[84] Karl J. Friston. What Is Optimal about Motor Control? , 2011, Neuron.
[85] Theresa J Klein,et al. A physical model of sensorimotor interactions during locomotion , 2012, Journal of neural engineering.
[86] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[87] Trevor Bekolay,et al. Supplementary Materials for A Large-Scale Model of the Functioning Brain , 2012 .
[88] Yuval Tassa,et al. Synthesis and stabilization of complex behaviors through online trajectory optimization , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[89] Baining Guo,et al. Terrain runner , 2012, ACM Trans. Graph..
[90] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[91] Zoran Popovic,et al. Discovery of complex behaviors through contact-invariant optimization , 2012, ACM Trans. Graph..
[92] S. Scott. The computational and neural basis of voluntary motor control and planning , 2012, Trends in Cognitive Sciences.
[93] Sergey Levine,et al. Guided Policy Search , 2013, ICML.
[94] Matthew Millard,et al. Flexing computational muscle: modeling and simulation of musculotendon dynamics. , 2013, Journal of biomechanical engineering.
[95] Vladlen Koltun,et al. Animating human lower limbs using contact-invariant optimization , 2013, ACM Trans. Graph..
[96] S. Sternson. Hypothalamic Survival Circuits: Blueprints for Purposive Behaviors , 2013, Neuron.
[97] L. Bonazzi,et al. Complex Movement Topography and Extrinsic Space Representation in the Rat Forelimb Motor Cortex as Defined by Long-Duration Intracortical Microstimulation , 2013, The Journal of Neuroscience.
[98] Hugo Merchant,et al. Motor system evolution and the emergence of high cognitive functions , 2014, Progress in Neurobiology.
[99] David J. Anderson,et al. Decoding Ventromedial Hypothalamic Neural Activity during Male Mouse Aggression , 2014, The Journal of Neuroscience.
[100] Emanuel Todorov,et al. Combining the benefits of function approximation and trajectory optimization , 2014, Robotics: Science and Systems.
[101] Andrew R. Brown,et al. Motor Cortex Is Functionally Organized as a Set of Spatially Distinct Representations for Complex Movements , 2014, The Journal of Neuroscience.
[102] L. F. Abbott,et al. Hierarchical Control Using Networks Trained with Higher-Level Forward Models , 2014, Neural Computation.
[103] Matthew T. Kaufman,et al. Supplementary materials for : Cortical activity in the null space : permitting preparation without movement , 2014 .
[104] Zengcai V. Guo,et al. Flow of Cortical Activity Underlying a Tactile Decision in Mice , 2014, Neuron.
[105] Richard Hans Robert Hahnloser,et al. Evidence for a causal inverse model in an avian cortico-basal ganglia circuit , 2014, Proceedings of the National Academy of Sciences.
[106] Ashesh K Dhawale,et al. Motor Cortex Is Required for Learning but Not for Executing a Motor Skill , 2015, Neuron.
[107] Scott T. Grafton,et al. The striatum: where skills and habits meet. , 2015, Cold Spring Harbor perspectives in biology.
[108] Zengcai V. Guo,et al. A motor cortex circuit for motor planning and movement , 2015, Nature.
[109] Zoran Popovic,et al. Interactive Control of Diverse Complex Characters with Neural Networks , 2015, NIPS.
[110] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[111] Stefano Ermon,et al. Generative Adversarial Imitation Learning , 2016, NIPS.
[112] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[113] Sergey Levine,et al. High-Dimensional Continuous Control Using Generalized Advantage Estimation , 2015, ICLR.
[114] Joshua B. Tenenbaum,et al. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation , 2016, NIPS.
[115] Yuval Tassa,et al. Learning and Transfer of Modulated Locomotor Controllers , 2016, ArXiv.
[116] Tom Schaul,et al. FeUdal Networks for Hierarchical Reinforcement Learning , 2017, ICML.
[117] J. Hodgins,et al. Learning to Schedule Control Fragments for Physics-Based Characters Using Deep Q-Learning , 2017 .
[118] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[119] Ryan Remedios,et al. Social Behaviour Shapes Hypothalamic Neural Ensemble Representations Of Conspecific Sex , 2017, Nature.
[120] Marcin Andrychowicz,et al. One-Shot Imitation Learning , 2017, NIPS.
[121] Xiao-Jing Wang,et al. Reward-based training of recurrent neural networks for cognitive and value-based tasks , 2016, bioRxiv.
[122] Joseph J. Paton,et al. A robust role for motor cortex , 2016, bioRxiv.
[123] Matthew T. Kaufman,et al. Perspectives on classical controversies about the motor cortex. , 2017, Journal of neurophysiology.
[124] Glen Berseth,et al. DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning , 2017, ACM Trans. Graph..
[125] Yuval Tassa,et al. Emergence of Locomotion Behaviours in Rich Environments , 2017, ArXiv.
[126] Pietro Perona,et al. Learning recurrent representations for hierarchical behavior modeling , 2016, ICLR.
[127] M. A. MacIver,et al. Neuroscience Needs Behavior: Correcting a Reductionist Bias , 2017, Neuron.
[128] Nando de Freitas,et al. Robust Imitation of Diverse Behaviors , 2017, NIPS.
[129] Yee Whye Teh,et al. Distral: Robust multitask reinforcement learning , 2017, NIPS.
[130] Tom Schaul,et al. Reinforcement Learning with Unsupervised Auxiliary Tasks , 2016, ICLR.
[131] Yuval Tassa,et al. Learning human behaviors from motion capture by adversarial imitation , 2017, ArXiv.
[132] Georg B. Keller,et al. Mouse Motor Cortex Coordinates the Behavioral Response to Unpredicted Sensory Feedback , 2018, Neuron.
[133] Sergey Levine,et al. DeepMimic , 2018, ACM Trans. Graph..
[134] K. Svoboda,et al. Neural mechanisms of movement planning: motor cortex and beyond , 2018, Current Opinion in Neurobiology.
[135] Scott W. Linderman,et al. The Striatum Organizes 3D Behavior via Moment-to-Moment Action Selection , 2018, Cell.
[136] Aaron C. Courville,et al. FiLM: Visual Reasoning with a General Conditioning Layer , 2017, AAAI.
[137] Yuval Tassa,et al. DeepMind Control Suite , 2018, ArXiv.
[138] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[139] Michaela Bruton,et al. Synergies in coordination: a comprehensive overview of neural, computational, and behavioral approaches. , 2018, Journal of neurophysiology.
[140] Joel Z. Leibo,et al. Unsupervised Predictive Memory in a Goal-Directed Agent , 2018, ArXiv.
[141] Nando de Freitas,et al. Reinforcement and Imitation Learning for Diverse Visuomotor Skills , 2018, Robotics: Science and Systems.
[142] Pierre-Yves Oudeyer,et al. Towards a neuroscience of active sampling and curiosity , 2018, Nature Reviews Neuroscience.
[143] Yee Whye Teh,et al. Information asymmetry in KL-regularized RL , 2019, ICLR.
[144] Scott W. Linderman,et al. Probabilistic Models of Larval Zebrafish Behavior: Structure on Many Scales , 2019, bioRxiv.
[145] Scott W. Linderman,et al. Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C. elegans , 2019, bioRxiv.
[146] Sergey Levine,et al. Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow , 2018, ICLR.
[147] Yee Whye Teh,et al. Neural probabilistic motor primitives for humanoid control , 2018, ICLR.
[148] Nicolas Heess,et al. Hierarchical visuomotor control of humanoids , 2018, ICLR.
[149] Joonho Lee,et al. Learning agile and dynamic motor skills for legged robots , 2019, Science Robotics.
[150] Sergey Levine,et al. Near-Optimal Representation Learning for Hierarchical Reinforcement Learning , 2018, ICLR.
[151] P. Cisek. Resynthesizing behavior through phylogenetic refinement , 2019, Attention, Perception, & Psychophysics.
[152] Mark L. Latash,et al. On the Construction of Movements , 2020 .
[153] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..