Do you know or have heard about any cutting edge deep reinforcement-learning algorithm which can be successfully applied for discrete action-spaces in multi-agent settings?
I have been researching and I have found MADDPG and Soft Q-learning algorithms as the top ones in the state-of-the-art. They are mainly focused on environments with continuous action space. Although they can be applied to discrete action-space (e.g. MADDPG with gumbel softmax) it seems it is not what they are intended for (I have tried with MADDPG (w/ Gumbel softmax) achieving disastrous results...). In their corresponding papers they don't give a lot of details of how to use them in these settings.