Towards a self-stopping evolutionary algorithm using coupling from the past
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Perfect simulation of monotone systems for rare event probability estimation
WSC '05 Proceedings of the 37th conference on Winter simulation
Perfect simulation and monotone stochastic bounds
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Different Monotonicity Definitions in Stochastic Modelling
ASMTA '09 Proceedings of the 16th International Conference on Analytical and Stochastic Modeling Techniques and Applications
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Multivariate linear recursions with Markov-dependent coefficients
Journal of Multivariate Analysis
Combinatorics, Probability and Computing
Stationary solution approximation using a memory-efficient perfect sampling technique
Proceedings of the 44th Annual Simulation Symposium
Opinion Fluctuations and Disagreement in Social Networks
Mathematics of Operations Research
Orbit distributions of iterated function systems with finitely many forms
Computers & Mathematics with Applications
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Iterated random functions are used to draw pictures or simulate large Ising models, among other applications. They offer a method for studying the steady state distribution of a Markov chain, and give useful bounds on rates of convergence in a variety of examples. The present paper surveys the field and presents some new examples. There is a simple unifying idea: the iterates of random Lipschitz functions converge if the functions are contracting on the average.