Multi-agent Reinforcement Learning Paper Reading UPDeT

If you are a freshman in the field of multi-agent reinforcement learning, the below links are all famous multi-agent reinforcement learning papers that I shared before. These papers are all about factorization in multi-agent problems, therefore, I believe you can learn more about multi-agent reinforcement learning before reading this article!!! Transfer learning has been widely used in many different machine learning fields, such as computer vision(object recognition, classification, etc) and natural language processing(translation, semantic analysis, etc), and has shown that transfer learning can significantly improve training efficiency. However, there is only a few research trying to apply transfer learning in multi-agent reinforcement learning problems. Recent advances in multi-agent reinforcement learning have largely limited training one model from scratch for every new task. This limitation occurs due to the restriction of the model architecture related to fixed input and output dimensions, which hinder the experience accumulation and transfer of the learned agent over tasks across diverse levels of difficulty.