算法A在分布式多联盟博弈中的三重优势

Compared to existing works on distributed multi-agent game theory, algorithm A has three advantages. Firstly, algorithm A incorporates the variable sample scale method to handle the interference caused by uncertain variables, and can suppress its impact on seeking Nash equilibrium. Secondly, algorithm A uses a scheme where agents estimate the strategies for each group, instead of estimating the strategies for all players as in existing works. Therefore, algorithm A greatly reduces the variable storage requirements, reducing it from nn to np. Thirdly, since the update of algorithm A only requires local and neighbor information, and does not have any initialization requirements, it is flexible and scalable, making it easy to implement and apply.