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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…
COBS is an Off-Policy Policy Evaluation (OPE) Benchmarking Suite. The goal is to provide fine experimental control to carefully tease out an OPE method's performance across many key conditions.
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
Official code for the "Towards Evaluating Adaptivity of Model-Based Reinforcement Learning" paper.
The main features of chandar-lab/loca2 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… clvoloshin/cobs — COBS is an Off-Policy Policy Evaluation (OPE) Benchmarking Suite. The goal is to provide fine experimental control to… cvdfoundation/kinetics-dataset — Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover… danijar/crafter — Status: Stable release. aravindr93/mjrl — This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
