Convergence results for the (1,\(\lambda\))-SA-ES using the theory of \(\varphi\)-irreducible Markov chains

DOI10.1016/j.tcs.2004.11.017zbMath1080.68113OpenAlexW1976503157WikidataQ56031316 ScholiaQ56031316MaRDI QIDQ1779296

Anne Auger

Publication date: 1 June 2005

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2004.11.017

zbMATH Keywords

Markov chainsConvergencecontinuous optimizationrandomized search heuristicsEvolution strategiesFoster-Lyapunov drift conditions

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Randomized algorithms (68W20)

Related Items (12)

Convergence Rates of Evolutionary Algorithms and Parallel Evolutionary Algorithms ⋮ Linear Convergence of Comparison-based Step-size Adaptive Randomized Search via Stability of Markov Chains ⋮ Quality gain analysis of the weighted recombination evolution strategy on general convex quadratic functions ⋮ On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling ⋮ Evolutionary self-adaptation: a survey of operators and strategy parameters ⋮ Average convergence rate of evolutionary algorithms in continuous optimization ⋮ Global linear convergence of evolution strategies with recombination on scaling-invariant functions ⋮ Lower bounds for comparison based evolution strategies using VC-dimension and sign patterns ⋮ Log-linear convergence and divergence of the scale-invariant \((1+1)\)-ES in noisy environments ⋮ Globally convergent evolution strategies ⋮ Efficient covariance matrix update for variable metric evolution strategies ⋮ Unnamed Item

Uses Software

• CMA-ES

Cites Work

• Markov chains and stochastic stability
• Global convergence for evolution strategies in spherical problems: Some simple proofs and difficulties.
• Convergence control methods for Markov chain Monte Carlo algorithms
• Stochastic algorithms
• Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
• Batch Size Effects in the Analysis of Simulation Output
• Convergence of simulated annealing using Foster-Lyapunov criteria
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