maddpg
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openai
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
In the source code, I saw some code about discrete actions. I changed act_space=MultiDiscrete（） to spaces.Discrete（）, but the output actions were not expected discrete numbers, but decimals, which made me...
When I ran python train.py --scenario simple, the reward function was too large, but I didn't change the code.
Hello, I have questions on exploration and Gumbel-Softmax. In the pseudocode, it mentioned initialize random process N for action exploration, which is same in the paper of DDPG. But I...
Hi, Thank you for releasing the code. I have some questions about the 'done' situation in the cooperative navigation environment. I don't see any done function for the env. I...
I went through the code and found a problem I didn't understand.  I think of p_reg as a regular term, and the regular term as a constraint on **the...
Hello! When I run the train.py file in the experiments directory according to your instructions, I execute the following command, python train.py --scenario simple After the training, I got the...
After walking through the code, I think, that there is a type here: https://github.com/openai/maddpg/blob/3ceefa0ada3ff31d633dd0bde8ff95213ce99be3/experiments/train.py#L141 Should be: ` agent_info[-1][i].append(info['n']) ` instead of `info_n['n']'.
Hello everybody! As far as I can see from the code, each agent maintains its own replay buffer. In the training step, when sampling the minibatch, the observations of all...
run code
I don't find code about "Inferring Policies of Ther Agents" and "Agent with Polivy Ensembles" mentioned in the paper 'Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments'.Did I miss something?
Has anyone adapted the code to run on Spark? Would be very grateful if it could be shared, or at least some pointers given. Or maybe it runs as-is?
