Evolving Neural Control Systems

Controlling unstable nonlinear systems with neural networks can be problematic. Two examples show that evolutionary programming provides a feasible method for addressing such control problems. >

[1]  Hans-Paul Schwefel,et al.  Numerical Optimization of Computer Models , 1982 .

[2]  C.W. Anderson,et al.  Learning to control an inverted pendulum using neural networks , 1989, IEEE Control Systems Magazine.

[3]  Alexis P. Wieland,et al.  Evolving Controls for Unstable Systems , 1991 .

[4]  David B. Fogel,et al.  Meta-evolutionary programming , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[5]  A. P. Wieland,et al.  Evolving neural network controllers for unstable systems , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[6]  Peter J. Angeline,et al.  An evolutionary algorithm that constructs recurrent neural networks , 1994, IEEE Trans. Neural Networks.

[7]  David B. Fogel,et al.  Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .