Robust imitation of diverse behaviors
WebReviews: Robust Imitation of Diverse Behaviors NIPS 2024 Mon Dec 4th through Sat the 9th, 2024 at Long Beach Convention Center Reviewer 1 The paper proposes a deep-learning … WebRobust Imitation of Diverse Behaviors Ziyu Wang, Josh Merel, Scott Reed, Greg Wayne, Nando de Freitas, Nicolas Heess In Advances in Neural Information Processing Systems (NIPS), Long Beach, 2024.
Robust imitation of diverse behaviors
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WebRobust Imitation of Diverse Behaviors Ziyu Wang , Josh Merel∗, Scott Reed, Greg Wayne, Nando de Freitas, Nicolas Heess DeepMind Joint First authors. Abstract Deep generative … WebRobust Imitation of Diverse Behaviors Publication Robust Imitation of Diverse Behaviors Download View publication Abstract Deep generative models have recently shown great …
WebNov 20, 2024 · GAIL is an efficient imitation learning method, and it can be extended to more complex environments. However, most of the current imitation learning methods [ 5, 6, 7] assume that the expert demonstrations has only one modality. We hope that the agent can learn from multi-modal expert demonstrations and get a policy with multiple modalities.
WebWe demonstrate the power of this approach by learning the motions produced by a motion graph constructed from eight hours of motion capture data and containing a diverse set of behaviors such as dancing (ballroom and breakdancing), Karate moves, gesturing, walking, and running. Supplemental Material 3386569.3392381.mp4 mp4 318.7 MB Webapproaches to imitation learning in a way that accentuates their individual strengths and addresses their limitations. The end product of this is a robust neural network policy that …
WebRaw Blame Learning Human Behaviors from Motion Capture by Adversarial Imitation This seems to be a follow-up paper to "Robust Imitation of Diverse Behaviors", which will appear at NIPS 2024. This one ("Learning Human Behaviors ...") is an arXiv preprint, so I wonder where it will eventually appear. They argue in the beginning that:
WebRobust Imitation of Diverse Behaviors. Basic idea: for imitation learning, combine strengths of generative models (GANs in the form of GAIL, VAEs, and autoregressive models) … to the mother of my future grandchildWebCompared to purely supervised methods, Generative Adversarial Imitation Learning (GAIL) can learn more robust controllers from fewer demonstrations, but is inherently mode-seeking and more difficult to train. In this paper, we show how to combine the favourable aspects of these two approaches. potato crackers bangladeshWebRobust imitation of diverse behaviours The third paper proposes a neural network architecture, building on state-of-the-art generative models, that is capable of learning the relationships between different behaviours and imitating specific actions that it is shown. to the most partWebmethods, Generative Adversarial Imitation Learning (GAIL) can learn more robust controllers from fewer demonstrations, but is inherently mode-seeking and more difficult to train. to the mountains by paul horganWebRobust Imitation of Diverse Behaviors Ziyu Wang , Josh Merel , Scott Reed, Greg Wayne, Nando de Freitas, Nicolas Heess DeepMind ziyu,jsmerel,reedscot,gregwayne,nandodefreitas,[email protected] Abstract potato council of kenyaWebthe learning robust towards compounding errors at unseen states. We show that our method signifi-cantly outperforms the state of the art across multi-ple experiments. 1Introduction … potato covered meatloafWebCompared to purely supervised methods, Generative Adversarial Imitation Learning (GAIL) can learn more robust controllers from fewer demonstrations, but is inherently mode … to the mountain and back