ES (Evolution Strategies)

ES is a class of black box optimization algorithms, as an alternative to popular MDP-based RL techniques such as Q-learning and Policy Gradients. It is invariant to action frequency and delayed rewards, tolerant of extremely long horizons, and does not need temporal discounting or value function approximation.

Installation

conda create -n rllib-es python=3.10
conda activate rllib-es
pip install -r requirements.txt
pip install -e '.[development]'

Usage

[ES Example]()