An Evolutionary Algorithm for Controlling Chaos: The Use of Multi-objective Fitness Functions

@inproceedings{Richter2002AnEA,
  title={An Evolutionary Algorithm for Controlling Chaos: The Use of Multi-objective Fitness Functions},
  author={Hendrik Richter},
  booktitle={PPSN},
  year={2002}
}
In this paper, we study an evolutionary algorithm employed to design and optimize a local control of chaos. In particular, we use a multi–objective fitness function, which consists of the objective function to be optimized and an auxiliary quantity applied as an additional driving force for the algorithm. Numerical results are presented illustrating the proposed scheme and showing the influence of employing such a multi–objective fitness function on convergence of the algorithm. 
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References

Publications referenced by this paper.
Showing 1-10 of 17 references

Optimization of local control of chaos by an evolutionary algorithm

Hendrik Richtera, Kurt J. Reinschkea
2000
View 5 Excerpts
Highly Influenced

Controlling chaos in unidimensional maps using macroevolutionary algorithms.

Physical review. E, Statistical, nonlinear, and soft matter physics • 2002
View 1 Excerpt

Multi-objective genetic programming for dynamic chaotic systems modelling

K. Rodriguez–Vázquez, P. J. Fleming
Congress on Evolutionary Computation, CEC’99, Washington, D.C., USA, • 1999
View 1 Excerpt

Local control of chaotic systems: A Lyapunov approach

H. Richter, K. J. Reinschke
Int. J. Bifurcation and Chaos 8 • 1998
View 1 Excerpt

Forecasting chaotic time series with genetic algorithms

G. G. Szpiro
Phys. Rev. E55 • 1997
View 2 Excerpts

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