MAPLE, Modular Attention for Interpretable and Prosocial Multi-Agent Reinforcement Learning
Feb 1, 2025
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1 min read
Tags:
- Reinforcement Learning
- Neuro-AI
- Multi-Agent Systems
- Modular Attention
Submitted to RLC 2025, and presented to NeurIPS 2023 (Meltingpot Challenge Workshop) and the Workshop of Advances in Neuro AI 2023. MAPLE introduces a novel approach to enhancing interpretability and performance in multi-agent reinforcement learning (MARL) through modular architecture and representation learning.
Documentation: https://drive.google.com/file/d/1aEcKU-kzjo8WxM_sjoJr9HGxAzQRVw4g/view?usp=sharing
