Dec 4, 2020 · We propose a novel way to learn latent world models by learning to predict sequences of future actions conditioned on task completion. These ...
Jan 12, 2021 · We propose a novel way to learn models in a latent space by learning to predict sequences of future actions conditioned on task completion.
We propose a novel way to learn latent world models by learning to predict sequences of future actions conditioned on task completion. These task-conditioned ...
These models track task-relevant environment dynamics over a distribution of tasks, while simultaneously serving as an effective heuristic for planning with ...
Dec 4, 2020 · This work proposes a novel way to learn latent world models by learning to predict sequences of future actions conditioned on task ...
Todo · Remove dependency on rlpyt and support normal gym environments. · Rewrite replay buffers to support non-visual goals. · Multi-processing for trajectory ...
Poster in. Workshop: Deep Reinforcement Learning. Poster: Planning from Pixels using Inverse Dynamics Models. Abstract: It appears you are a search engine ...
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Sep 10, 2024 · This research proposes a novel approach for the residual modeling of inverse dynamics employed to control a real robotic device. Specifically, ...
Contributed Talk: Planning from Pixels using Inverse Dynamics Models. Keiran Paster · Sheila McIlraith · Jimmy Ba. Abstract: It appears you are a search ...
Planning from Pixels using Inverse Dynamics Models. Paster, K., McIlraith, S. A., & Ba, J. In International Conference on Learning Representations (ICLR), ...