Before revision: In this paper, we propose actor-critic approaches by introducing an actor policy on QMIX 9 , which can remove the monotonicity constraint of QMIX and implement a non-monotonic value function factorization for  joint action-value .
After revision: Multi-agent value-based approaches recently make great progress, especially value decomposition methods. However, there are still a lot of limitations in value function factorization. In VDN, the joint action-value function is the sum of per-agent action-value function while the joint action-value function of QMIX is the monotonic mixing of per-agent action-value function. To some extent, QTRAN reduces the limitation of joint action-value functions that can be represented, but it has unsatisfied performance in complex tasks. In this paper, we propose actor-critic approaches by introducing an actor policy on QMIX 9 , which can remove the monotonicity constraint of QMIX and implement a non-monotonic value function factorization for joint action-value .