MAPPO vs IPPO in adversarial multi-agent RL — alternating, population, and league self-play in a custom predator-prey gridworld
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Updated
Apr 7, 2026 - Python
MAPPO vs IPPO in adversarial multi-agent RL — alternating, population, and league self-play in a custom predator-prey gridworld
🎯 Key Features 1. Flexible Game Configuration Adjustable grid size (3×3 up to 10×10) Customizable win condition (e.g., 5-in-a-row on a 7×7 board) 2. Two Competing RL Agents Agent 1 (Blue X) vs Agent 2 (Red O) Each has independent Q-Learning parameters Watch them evolve different strategies over time
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