After an accepted line-search step, the solver has already rebuilt the gradient
and Hessian and solved for the next search direction, so the Newton decrement
0.5*g'*H^-1*g -- the quadratic model's predicted cost improvement of the next
iteration -- costs one dot product. Terminating when it falls below tolerance
avoids running one more iteration only to observe a correspondingly small
actual improvement.
This is a C port of Alain's proposal in MJWarp:
https://github.com/google-deepmind/mujoco_warp/pull/1520
PiperOrigin-RevId: 947768034
Change-Id: I94e5c71a4e2b4a7775611edd1dad254bba2633b4
Yuval Tassa
1e66efd114