Imitation
Related papers: 20
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Imitation learning is a machine learning paradigm in which an agent acquires skills by observing and replicating demonstrations provided by an expert, typically a human, rather than by manually programming behaviors or relying solely on trial-and-error reinforcement signals. In robotics, it encompasses techniques such as programming by demonstration, behavioral cloning, and learning from observation, where a robot extracts generalizable motion patterns, force profiles, or decision policies from recorded or live demonstrations and reproduces them across varied contexts. Approaches range from dynamical movement primitives and hidden Markov models for gesture reproduction to deep neural networks that map raw sensor inputs directly to control actions in domains like autonomous driving and dexterous manipulation. Imitation learning matters because specifying complex robot behavior through explicit programming becomes intractable in unstructured, real-world environments. By grounding learning in human expertise, it dramatically reduces the engineering burden, accelerates skill acquisition, and enables robots to handle nuanced tasks—from assembly and teleoperated manipulation to social interaction with children with autism—that would otherwise require prohibitively detailed hand-crafted rules.
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Is imitation learning the route to humanoid robots?
Stefan Schaal
Citations: 1325 • 1999
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
Sylvain Calinon, F. Guenter, Aude Billard
Citations: 1086 • 2007
End-to-end driving via conditional imitation learning
Felipe Codevilla, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy
Citations: 1065
Imitation Learning
Ahmed Hussein, Mohamed Medhat Gaber, Eyad Elyan, Chrisina Jayne
Citations: 1014 • 2017
Robot Programming by Demonstration
Aude Billard, Sylvain Calinon, Rüdiger Dillmann, Stefan Schaal
Citations: 984 • 2008
Movement imitation with nonlinear dynamical systems in humanoid robots
Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal
Citations: 842 • 2003
Imitation in Animals and Artifacts
Citations: 708 • 2002
Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills?
Ben Robins, Kerstin Dautenhahn, René te Boekhorst, Aude Billard
Citations: 686 • 2005
Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors
Liu Jun, Huihong Chang, Jeffrey Yi‐Lin Forrest, Baohua Yang
Citations: 631 • 2020
Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation
Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, Pieter Abbeel
Citations: 590 • 2018
The Cog Project: Building a Humanoid Robot
Rodney A. Brooks, Cynthia Breazeal, Matthew Marjanović, Brian Scassellati, Matthew M. Williamson
Citations: 572 • 1999
Time-Contrastive Networks: Self-Supervised Learning from Video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine, Google Brain
Citations: 555 • 2018
The Imitative Mind: Development, Evolution and Brain Bases
Andrew N. Meltzoff, Wolfgang Prinz
Citations: 541 • 2002
Learning and Reproduction of Gestures by Imitation
Sylvain Calinon, Florent D'halluin, Eric L. Sauser, Darwin G. Caldwell, Aude Billard
Citations: 455 • 2010
Towards interactive robots in autism therapy
Kerstin Dautenhahn, Iain Werry
Citations: 455 • 2004
Robots that imitate humans
Cynthia Breazeal, Brian Scassellati
Citations: 422 • 2002
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
Guillaume Sartoretti, Justin Kerr, Yunfei Shi, Glenn Wagner, T. K. Satish Kumar, Sven Koenig, Howie Choset
Citations: 399 • 2019
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters
Citations: 379 • 2018
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters
Citations: 370 • 2018
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Aleš Ude, Andrej Gams, Tamim Asfour, Jun Morimoto
Citations: 357 • 2010