An evolved, vision-based behavioral model of coordinated group motion
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Genetic Algorithms in Noisy Environments
Machine Learning
Strongly Typed Genetic Programming in Evolving Cooperation Strategies
Proceedings of the 6th International Conference on Genetic Algorithms
Promoting Generalisation of Learned Behaviours in Genetic Programming
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Evolution Strategies on Noisy Functions: How to Improve Convergence Properties
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Creating Robust Solutions by Means of Evolutionary Algorithms
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Genetic algorithms, selection schemes, and the varying effects of noise
Evolutionary Computation
Robustness of robot programs generated by genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Generality versus size in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Methods for evolving robust programs
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Genetic programming, validation sets, and parsimony pressure
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
On the robustness of population-based versus point-basedoptimization in the presence of noise
IEEE Transactions on Evolutionary Computation
Genetic programming and evolutionary generalization
IEEE Transactions on Evolutionary Computation
Technical market indicators optimization using evolutionary algorithms
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
A tree-based GA representation for the portfolio optimization problem
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Application of a Memetic Algorithm to the Portfolio Optimization Problem
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Using memetic algorithms to improve portfolio performance in static and dynamic trading scenarios
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Behavioural GP diversity for adaptive stock selection
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Multiobjective optimization of technical market indicators
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Evolving a robust trader in a cyclic double auction market
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Fitness function evaluation for MA trading strategies based on genetic algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Artificial Intelligence Review
A parallel evolutionary algorithm for technical market indicators optimization
Natural Computing: an international journal
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Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive) are dynamic, unpredictable and unforgiving. How can GP be improved so that solutions are produced that are robust to non-trivial changes in the environment? We explore an approach that uses subsets of extreme environments during training.