3 citations · 4 across the 2 of their papers we have counts for
3 papers
Scalarization via utility functions in multi-objective optimization
Lorenzo Lampariello, Simone Sagratella, Valerio Giuseppe Sasso +1
We study a general scalarization approach via utility functions in multi-objective optimization. It consists of maximizing utility which is obtained from the objectives' bargaining…
Best-response algorithms for a class of monotone Nash equilibrium problems with mixed-integer variables
Filippo Fabiani, Simone Sagratella
We characterize the convergence properties of traditional best-response (BR) algorithms in computing solutions to mixed-integer Nash equilibrium problems (MI-NEPs) that turn into a…
A gray-box approach for curriculum learning
Francesco Foglino, Matteo Leonetti, Simone Sagratella +1
Curriculum learning is often employed in deep reinforcement learning to let the agent progress more quickly towards better behaviors. Numerical methods for curriculum learning in t…