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Legged robots operating in real-world environments must possess the ability to rapidly adapt to unexpected conditions, such as changing terrains and varying payloads.
Legged robots that balance (MIT press, 1986)
Raibert, M. H · 1986
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Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E. & Williams, R. J · 1986
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Spike-timing-dependent plasticity: common themes and divergent vistas
Kepecs, A., Van Rossum, M. C., Song, S. & Tegner, J · 2002
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Bigdog, the rough-terrain quadruped robot
Raibert, M., Blankespoor, K., Nelson, G. & Playter, R · 2008
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Synaptic plasticity: multiple forms, functions, and mechanisms
Citri, A. & Malenka, R. C · 2008
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Spike timing–dependent plasticity: a hebbian learning rule
Caporale, N. & Dan, Y · 2008
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Implementing spike-timing-dependent plasticity on spinnaker neuromorphic hardware
Jin, X., Rast, A., Galluppi, F., Davies, S. & Furber, S · 2010
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Spinnaker: A 1-w 18-core system-on-chip for massively-parallel neural network simulation
Painkras, E. et al · 2013
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Optimization based full body control for the atlas robot
Feng, S., Whitman, E., Xinjilefu, X. & Atkeson, C. G · 2014
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Unsupervised learning of an efficient short-term memory network
Vertechi, P., Brendel, W. & Machens, C. K · 2014
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Neuronal dynamics: From single neurons to networks and models of cognition (Cambridge University Press, 2014)
Gerstner, W., Kistler, W. M., Naud, R. & Paninski, L · 2014
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High-dimensional continuous control using generalized advantage estimation
Schulman, J., Moritz, P., Levine, S., Jordan, M. & Abbeel, P · 2015
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Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
Kuindersma, S. et al · 2016
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Convolutional networks for fast, energy-efficient neuromorphic computing
Esser, S. K. et al · 2016
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Neuromodulated spike-timing-dependent plasticity, and theory of three-factor learning rules
Frémaux, N. & Gerstner, W · 2016
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Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A. & Klimov, O · 2017
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Loihi: A neuromorphic manycore processor with on-chip learning
Davies, M. et al · 2018
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Eligibility traces and plasticity on behavioral time scales: experimental support of neohebbian three-factor learning rules
Gerstner, W., Lehmann, M., Liakoni, V., Corneil, D. & Brea, J · 2018
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Structural learning in artificial neural networks using sparse optimization
Manngård, M., Kronqvist, J. & Böling, J. M · 2018
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Spikepropamine: Differentiable plasticity in spiking neural networks
Schmidgall, S., Ashkanazy, J., Lawson, W. & Hays, J · 2021
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Rma: Rapid motor adaptation for legged robots
Kumar, A., Fu, Z., Pathak, D. & Malik, J · 2021
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Synaptic plasticity as bayesian inference
Aitchison, L. et al · 2021
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Self-constructing neural networks through random mutation
Schmidgall, S · 2021
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Learning to walk in minutes using massively parallel deep reinforcement learning
Rudin, N., Hoeller, D., Reist, P. & Hutter, M · 2022
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Bellec, G. et al · 2019
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Cellular automata as convolutional neural networks
Gilpin, W · 2019
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Data efficient reinforcement learning for legged robots
Yang, Y. et al · 2020
Cited alongside, same era.
Learning quadrupedal locomotion over challenging terrain
Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V. & Hutter, M · 2020
Cited alongside, same era.
Perspectives on sim2real transfer for robotics: A summary of the r: Ss 2020 workshop
Höfer, S. et al · 2020
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Synaptic plasticity dynamics for deep continuous local learning (decolle)
Kaiser, J., Mostafa, H. & Neftci, E · 2020
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A solution to the learning dilemma for recurrent networks of spiking neurons
Bellec, G. et al · 2020
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Pehle, C. et al · 2022
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Brain-inspired global-local learning incorporated with neuromorphic computing
Wu, Y. et al · 2022
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Adapting rapid motor adaptation for bipedal robots
Kumar, A. et al · 2022
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Learning to learn online with neuromodulated synaptic plasticity in spiking neural networks
Schmidgall, S. & Hays, J · 2022
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Hypernca: Growing developmental networks with neural cellular automata
Najarro, E., Sudhakaran, S., Glanois, C. & Risi, S · 2022
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Legged locomotion in challenging terrains using egocentric vision
Agarwal, A., Kumar, A., Malik, J. & Pathak, D · 2023
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In-hand object rotation via rapid motor adaptation
Qi, H., Kumar, A., Calandra, R., Ma, Y. & Malik, J · 2023
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Deep whole-body control: learning a unified policy for manipulation and locomotion
Fu, Z., Cheng, X. & Pathak, D · 2023
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Meta-spikepropamine: Learning to learn with synaptic plasticity in spiking neural networks
Schmidgall, S. & Hays, J · 2023
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