Gambler’s Ruin Model and Ga
نویسنده
چکیده
In order to estimate the correct size of population, estimations of population sizing have been used in the genetic algorithms (GAs). The estimation considers a test function being optimized, a representation of individuals and a character of used operators. By means of the estimation model the right population size with taking into account the final overall quality of individuals is identified. This article extends the Gambler’s ruin model (GRM) by a new equation for convergence time.
منابع مشابه
Gambler’s Ruin with Catastrophes and Windfalls
We compute ruin probabilities, in both infinite-time and finite-time, for a Gambler’s Ruin problem with both catastrophes and windfalls in addition to the customary win/loss probabilities. For constant transition probabilities, the infinite-time ruin probabilities are derived using difference equations. Finite-time ruin probabilities of a system having constant win/loss probabilities and variab...
متن کاملOptimal Sampling and Speed-Up for Genetic Algorithms on the Sampled OneMax Problem
This paper investigates the optimal sampling and the speed-up obtained through sampling for the sampled OneMax problem. Theoretical and experimental analyses are given for three different population-sizing models: the decision-making model, the gambler’s ruin model, and the fixed population-sizing model. The results suggest that, when the desired solution quality is fixed to a high value, the d...
متن کاملChange-point detection of two-sided alternatives in the Brownian motion model and its connection to the gambler’s ruin problem with relative wealth perception
متن کامل
Gambler’s Ruin Problem with Relative Wealth Perception
We consider a modified version of Gambler’s Ruin Problem in which the gambler decides to quit based on the relative change of his or her wealth. For this purpose we consider two possible changes of wealth, namely the upward rally and the downward fall. We define upward rally as the difference of the current wealth and its historical minimum, while the downward fall is the difference of the hist...
متن کاملRe-seeding invalidates tests of random number generators
Kim et al (Appl Math & Comput 199 (2008) 195) recently presented a test of random number generators based on the gambler’s ruin problem and concluded that several generators, including the widely used Mersenne Twister, have hidden defects. We show here that the test by Kim et al suffers from a subtle, but consequential error: Re-seeding the pseudorandom number generator with a fixed seed for ea...
متن کامل