Hi,
First of all let me explain that I am aware that Unity offers some libraries related with RL, but they are oriented to agents, while the approach that I am looking for is completely different.
I am developing a strategic AI for a RTS. This strategic AI considers a bunch of parameters to weight its goals and send orders to the units. I would like to optimize this weighting by using Neural Networks with Reinforcement Learning. However, to achieve this I need to make thousands of simulations of the game and Unity is not designing thinking in something like that.
However, I wonder how can I speed up the game to work much faster without breaking it. I have though about increasing a lot the TimeScale but it has some incoveniences. Because it makes actions go faster, it results in less FPS per action, with can be a huge loss in precision. If for example a unit is moving towards a position it is not the same to do it in 500 frames than in 5, because in the middle of the path there might be some considerations.
To speedup I can only think about to prescind of everything related to rendering, but it is not enough.
Has anyone tried to do anything like this with Unity?
This is the approach that algorithms like AlphaGo follow, but as you know simulating Go is way easier. Yes, there is this thing of AlphaStar, so I wonder how many programmers where creating the simulation world.
Thanks!