MindGames Arena Generalization Track: In2AI Solution with Delayed Per-Step Reward Attribution

This research introduces a novel delayed per-step reward attribution method for training language model agents in multi-agent strategic interactions. It addresses the challenge of entangled outcomes by computing rewards at episode end and backpropagating them, enabling stable and sample-efficient reinforcement learning.