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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

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