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Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box function. This type of optimization is used across scientific and engineering disciplines in ways such as designing proteins and DNA sequences with particular…
Official code for the "Towards Evaluating Adaptivity of Model-Based Reinforcement Learning" paper.
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions…
The main features of cvdfoundation/kinetics-dataset are: Reinforcement Learning Environments.
Projects with overlapping indexed features include: benelot/pybullet-gym — PyBullet Gymperium. brandontrabucco/design-bench — Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that… chandar-lab/loca2 — Official code for the "Towards Evaluating Adaptivity of Model-Based Reinforcement Learning" paper. clvoloshin/cobs — COBS is an Off-Policy Policy Evaluation (OPE) Benchmarking Suite. The goal is to provide fine experimental control to… danijar/crafter — Status: Stable release. aravindr93/mjrl — This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
