The algorithm proposed is quite simple: it queries a point repeatedly, until it learns the sign of the gradient of the reward function, or at least with arbitrarily high probability. Then it proceeds to the next step of a standard binary search.
It allows individuals to randomly enlarge their search radiuses in the search process and to have more chances to jump out of the likely local optima when ...
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What is a stochastic search algorithm?
What is stochastic local search algorithms an overview?
Stochastic fractal search algorithm, a relatively efficient algorithm has certain advantages in solving multi-objective optimization problems.
As with all stochastic search algo- rithms, there are adjustable algorithm coefficients that must be specified, and that can have a profound effect on algorithm ...
Large scale optimisation problems are often tackled using stochastic adaptive search algorithms, but the convergence of such methods to the global optimum is ...
Abstract: A new population-based stochastic search algorithm is developed which automatically adjusts search domains of individuals in terms of current search ...
Gradient-based Adaptive Stochastic Search (GASS) is a new stochastic search optimization algorithm that has recently been proposed.
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Jan 18, 2020 · This article summarizes recent research and motivates future work on adaptive stochastic optimization methods, which have the potential to offer significant ...
The aim of this paper is to present a random search algorithm, Adaptive Stochastic Descent (ASD), that was inspired by manual parameter fitting and is ...
In this paper, we propose a stochastic search algorithm for solving general optimization problems with little structure. The algorithm iteratively finds ...