What are the strategies for computationally heavy environments or long-time waiting environments?

I have an environment that is computationally heavy (takes several seconds to get a reward and next state). This limits reinforcement capability, due to poor sampling of the problem. There is any strategy that could be used to address the problem (e.g. If I can use the environment in parallel, then I could use a multi-agent approach)

• Mltiple environments, installing some form of reward shaping or prior knowledge into the problem? – FourierFlux Sep 22 '20 at 18:28
• @FourierFlux In terms of multiple environments - then how you would integrate them? Average updates like in A3C alg. ? – Daniel Wiczew Sep 23 '20 at 14:53