Structured Action Reinforcement Learning (SARL)

⚠️ SARL is pre-release software, in active development!

SARL is a toolkit for performing reinforcement learning on environments with parameterised action spaces. Such action-spaces differ from the non-hierarchical, exclusively discrete or continuous action-spaces explored in conventional reinforcement learning.

A parameterized action-space, requires an agent to select from a discrete set of actions, then specify a continuous vector from that action's corresponding parameter-space (Masson et. al. 2016).

Contents

Baselines

• P-DQN

Environments

• Platform
• Goal

Usage

Instructions for use on Linux, Mac OSX, or Windows (via WSL).

• Ensure Python is installed python --version
• Ensure Poetry is installed poetry --version
  • You can install poetry with curl -sSL https://install.python-poetry.org | python3 -
  • Full instructions and alternative methods can be found here
• Clone this repository git clone https://github.com/ttollet/SARL.git
• Change directory cd SARL
• Install dependencies to virtual environment poetry install
• Check functionality poetry run pytest
• Enter virtual environment with poetry shell
  • Exit the virtual environment with exit

## Examples

python3 sarl/train.py algorithm=ppo-ppo environment=platform hydra.job.name=ppo-ppo-platform parameters.learning_steps=540000 parameters.seeds=[1] parameters.cycles=600