I like it. On a meta level, giving the machine a bit of a priori knowledge about the shape of things to come, that makes a lot of sense.

When the self-driving car hits an obstacle, they will both obey mostly Newtonian sums.

Effectively embedding that knowledge (the differential equations) might make the system less useful for other applications, but should very cheaply improve it's chances on a lot of real-world problems.

Robotics is largely done with PID feedback things. Some more understanding of the behaviour of springs etc etc should help a lot. Quite possibly in other domains, hard to know where such things apply.