Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
| Hi-index | 0.00 |
This paper presents the result for Simultaneous Perturbation Stochastic Approximation (SPSA) on the BBOB 2010 noisy testbed. SPSA is a stochastic gradient approximation strategy which uses random directions for the gradient estimate. The paper describes the steps performed by the strategy and the experimental setup. The chosen setup represents a rather basic variant of SPSA. The strategy can successfully solve 5 functions for D = 2, 2 for D = 3, and 1 for D = 5. For each function at least one target level is reached up to D = 3.