2.2k citations · 3.1k across the 17 of their papers we have counts for
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cs.LG2021★ 4 cited
Procedural Generalization by Planning with Self-Supervised World Models
Ankesh Anand, Jacob Walker, Yazhe Li +5
One of the key promises of model-based reinforcement learning is the ability to generalize using an internal model of the world to make predictions in novel environments and tasks.…
cs.LG2021
Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi +3
Recent developments in the field of model-based RL have proven successful in a range of environments, especially ones where planning is essential. However, such successes have been…
cs.LG2021★ 2 cited
Pretrained Encoders are All You Need
Mina Khan, P Srivatsa, Advait Rane +4
Data-efficiency and generalization are key challenges in deep learning and deep reinforcement learning as many models are trained on large-scale, domain-specific, and expensive-to-…