Parallel Training of Multiple RL Agents in same environment

In the context of Reinforcement Learning Toolbox, it is possible to set "UseParallel" to "true" within "rlTrainingOptions" in order to run multiple simulations in parallel and improve the training speed for the agent.

However, if my goal is to train multiple agents in same environment I have to use "rlMultiAgentTrainingOptions" in order to specify my options. According to the documentation, this object does not have a "UseParallel" property. Does this mean that parallel training is currently not supported for multi-agent scenario? If this is the case, is there a known workaround for this?

Answer 1

[Emmanouil Tzorakoleftherakis]

Parallel training is currently not supported for multi-agent reinforcement learning. One thing you could do is train the agents sequentially in parallel, but this will only work if the agents are "decoupled", i.e. they operate on different components on the environment and can thus be trained separately.

[Federico Toso]

Ok thank you very much!