FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
A variant of the augmented Lagrangian-type algorithm for strictly convex quadratic programming problems with bounds and equality constraints is considered. The algorithm exploits the adaptive ...
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