Efficient GA Based Techniques for Classification
Applied Intelligence
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
Population-Based Learning: A Method for Learning from Examples Under Resource Constraints
IEEE Transactions on Knowledge and Data Engineering
Optimization of Noisy Fitness Functions by Means of Genetic Algorithms Using History of Search
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Efficiency and Mutation Strength Adaptation of the (mu, muI, lambda)-ES in a Noisy Environment
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
A Fitness Estimation Strategy for Genetic Algorithms
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Genetic Algorithm and Social Simulation
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
History and Immortality in Evolutionary Computation
Selected Papers from the 5th European Conference on Artificial Evolution
Advances in evolutionary computing
Efficient Genetic Algorithms Using Discretization Scheduling
Evolutionary Computation
Simulation optimization using tabu search: an emperical study
WSC '05 Proceedings of the 37th conference on Winter simulation
Multi-sensor fusion: an Evolutionary algorithm approach
Information Fusion
A clustering entropy-driven approach for exploring and exploiting noisy functions
Proceedings of the 2007 ACM symposium on Applied computing
Diverse committees vote for dependable profits
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolving robust GP solutions for hedge fund stock selection in emerging markets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Scheduling of genetic algorithms in a noisy environment
Evolutionary Computation
Genetic algorithms as global random search methods: An alternative perspective
Evolutionary Computation
Genetic algorithms, selection schemes, and the varying effects of noise
Evolutionary Computation
A Steady-State Genetic Algorithm with Resampling for Noisy Inventory Control
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Differential Evolution with Noise Analyzer
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Localization for solving noisy multi-objective optimization problems
Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Selection in the presence of noise
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
ICES'07 Proceedings of the 7th international conference on Evolvable systems: from biology to hardware
A differential evolution for optimisation in noisy environment
International Journal of Bio-Inspired Computation
Heuristics for sampling repetitions in noisy landscapes with fitness caching
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Bandit-based estimation of distribution algorithms for noisy optimization: rigorous runtime analysis
LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
Discovering process models with genetic algorithms using sampling
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
An evolutionary computing approach to robust design in the presence of uncertainties
IEEE Transactions on Evolutionary Computation
Accumulative sampling for noisy evolutionary multi-objective optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
The effects of selection on noisy fitness optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Distributed genetic process mining using sampling
PaCT'11 Proceedings of the 11th international conference on Parallel computing technologies
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
On the prediction of the solution quality in noisy optimization
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Genetic algorithms with noisy fitness
Mathematical and Computer Modelling: An International Journal
Cooperative games in marketing: a differential game approach
Neural, Parallel & Scientific Computations
A VNS algorithm for noisy problems and its application to project portfolio analysis
SAGA'07 Proceedings of the 4th international conference on Stochastic Algorithms: foundations and applications
Deriving a robust policy for container stacking using a noise-tolerant genetic algorithm
Proceedings of the 2012 ACM Research in Applied Computation Symposium
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Genetic algorithms are adaptive search techniques which have been used to learn high-performance knowledge structures in reactive environments that provide information in the form of payoff. In general, payoff can be viewed as a noisy function of the structure being evaluated, and the learning task can be viewed as an optimization problem in a noisy environment. Previous studies have shown that genetic algorithms can perform effectively in the presence of noise. This work explores in detail the tradeoffs between the amount of effort spent on evaluating each structure and the number of structures evaluated during a given iteration of the genetic algorithm. Theoretical analysis shows that, in some cases, more efficient search results from less accurate evaluations. Further evidence is provided by a case study in which genetic algorithms are used to obtain good registrations of digital images.