Authors: Aragone, L.S.; Gianatti, J.; Lotito, P.A.; Parente, L.A.
Title: Stochastic Descent vs Sample Average in Uncertain Minimax Control Problems.
Resumen: We propose a stochastic descent algorithm for solving uncertain minimax control problems. At each iterate, the scheme randomly draws a sample point from the underlying probability space, computes a feasible direction and performs an Armijo step in order to obtain the next iterate. On some simple examples, we compare its performance with a descent algorithm based on sample average approximations, obtaining promissory numerical results.
Meeting type: Congreso.
Type of job: Artículo Breve.
Production: Stochastic Descent vs Sample Average in Uncertain Minimax Control Problems.
Scientific meeting: MACI.
Meeting place: Comodoro Rivadavia.
Organizing Institution: ASAMACI.
It's published?: Yes
Publication place: Comodoro Rivadavia
Meeting month: 5