We invite researchers to perform a more qualitative measure of Brax’s physics fidelity by training their own policies in the Brax Training Colab. The learned trajectories are recognizably similar to those seen in OpenAI Gym. Why would the comparison be qualitative? We have known equations of motion. Seems like it would be more productive to produce a quantitative metric where we compare the output to the theoretical…
You have to integrate which means discretizing time. And you have to deal with collision and solve constraints. There are no exact solutions in physics simulation.
Speeding Up Reinforcement Learning with a New Physics Simulation Engine
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Re: Speeding Up Reinforcement Learning with a New Physics Simulation Engine
#12Earlier quoted context omitted.
You have to integrate which means discretizing time. And you have to deal with collision and solve constraints. There are no exact solutions in physics simulation.
A computer simulation by definition is not exact because it is discretized. However it is still possible to solve mathematical formulae and use them to validate the AI based solution. This is done every day in the physical infrastructure you use and works extremely well. The planes you fly in to the submarine cables Internet traffic is carried on are all modeled numerically. They aren’t modeled using AI ( at least no…
Re: Speeding Up Reinforcement Learning with a New Physics Simulation Engine
#13Earlier quoted context omitted.
A computer simulation by definition is not exact because it is discretized. However it is still possible to solve mathematical formulae and use them to validate the AI based solution. This is done every day in the physical infrastructure you use and works extremely well. The planes you fly in to the submarine cables Internet traffic is carried on are all modeled numerically. They aren’t modeled using AI ( at least no…
this isn’t an AI based physics simulator. It’s a normal physical simulator for use in AI