An environment for reproducing dominance hierarchies in RL agents
Project description
Chicken Coop
Supports Python 3.11.
Usage instructions:
# Set up virtualenv if needed:
python -m venv chicken-coop-env
source chicken-coop-env/bin/activate
# Install Chicken Coop:
pip install chicken-coop
# Run tests:
pytest
# Basic run:
python -m chicken_coop run
# Main run used in the paper:
python -m chicken_coop run --moniker paper-run --use-tune --n-tune-samples 300
# Transplant a visitor population into a resident population:
python -m chicken_coop transplant --moniker paper-transplant \
--visitor-trek ~/.chicken_coop/<YOUR_PREVIOUS_RUN>
# Ablate opponent perception accuracy:
python -m chicken_coop run --moniker paper-ablate-observation --use-tune --n-tune-samples 10 \
--observation-accuracy 0.0 \
--observation-accuracy 0.1 \
--observation-accuracy 0.2 \
--observation-accuracy 0.3 \
--observation-accuracy 0.4 \
--observation-accuracy 0.5 \
--observation-accuracy 0.6 \
--observation-accuracy 0.7 \
--observation-accuracy 0.8 \
--observation-accuracy 0.9 \
--observation-accuracy 1.0
# Investigate non-linearity:
python -m chicken_coop run --moniker paper-cycles --use-tune --n-tune-samples 30 --n-agents 12 \
--learning-rate 3e-05
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
chicken_coop-0.0.2.tar.gz
(48.6 kB
view hashes)
Built Distribution
Close
Hashes for chicken_coop-0.0.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 155b8905b79e55468c7bfab7b999c5097e741437ccb7d8983bcbaa357e25bd0b |
|
MD5 | 7c41f16a591ec1af1c8fbc210924697b |
|
BLAKE2b-256 | 04851c8ccf24fe9ea44002093ef2abdf965883599b3a2314f8824d72e48ed2be |