Omkar2118/datasets huggingface dataset:
QDax

**QDax** is a benchmark suite designed for for Deep Neuroevolution in Reinforcement Learning domains for robot control. The suite includes the definition of tasks, environments, behavioral descriptors, and fitness. It specify different benchmarks based on the complexity of both the task and the agent controlled by a deep neural network. The benchmark uses standard Quality-Diversity metrics, including coverage, QD-score, maximum fitness, and an archive profile metric to quantify the relation between coverage and fitness.

Source: [Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning](https://arxiv.org/pdf/2211.02193v1.pdf)

Image Source: [https://arxiv.org/pdf/2211.02193v1.pdf](https://arxiv.org/pdf/2211.02193v1.pdf)

Introducing paper: Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning