How smarino76/kaggriculture works
This repository implements a Kaggriculture game-playing agent. The environment supplies an observation; agent.py updates domain experts, applies its farming and market rules, and returns farmer and market actions. The experts analyze financial, agricultural, inventory, market, and livestock state, though the sampled policy primarily makes decisions directly from the observation. features.py offers separate time and farm feature extraction. The README is empty, and unsampled code limits confidence about additional integrations or how feature extraction is consumed.
Main entry points: agent.py Agent policy · business.py Livestock expert
Components 8
Agent policy
- Agent policy
agent.py
State analysis
- Financial expert
experts/business.py - Agriculture expert
experts/business.py - Inventory expert
experts/business.py - Market expert
experts/business.py - Livestock expert
experts/business.py - Feature extraction
features.py
Other components
- Kaggriculture environment
Connections 8
- Kaggriculture environment → Agent policy: sends observation
- Agent policy → Kaggriculture environment: returns actions
- Agent policy → Financial expert: updates state
- Agent policy → Agriculture expert: updates state
- Agent policy → Inventory expert: updates state
- Agent policy → Market expert: updates state
- Agent policy → Livestock expert: updates state
- Agent policy → Livestock expert: reads debug features