Hi, I have been doing the udacity deep-reinforcement-learning nanodegree and I came out with a doubt. 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 22 and Soft Q-learning 19 algorithms as the top ones in the state-of-the-art. I implemented the first one over an Unity environment and works well! However, 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.
Can somebody help me with this?