Balancing Rotators with Evolved Neurocontrollers

نویسندگان

  • Frank Pasemann
  • Ulf Dieckmann
چکیده

The presented evolutionary algorithm is especially designed to generate recurrent neural networks with non trivial internal dynam ics It is not based on genetic algorithms and sets no constraints on the number of neurons and the architecture of a network Network topol ogy and parameters like synaptic weights and bias terms are developed simultaneously It is well suited for generating neuromodules acting in sensorimotor loops and therefore it can be used for evolution of neuro controllers solving also nonlinear control problems We demonstrate this capability by applying the algorithm successfully to the following task Stabilize a rotating pendulum that is mounted on a cart in an upright position

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

F Ur Mathematik in Den Naturwissenschaften Leipzig Balancing Rotators with Evolved Neurocontrollers Balancing Rotators with Evolved Neurocontrollers

The presented evolutionary algorithm is especially designed to generate recurrent neural networks with non-trivial internal dynamics. It is not based on genetic algorithms, and sets no constraints on the number of neu-rons and the architecture of a network. Network topology and parameters like synaptic weights and bias terms are developed simultaneously. It is well suited for generating neuromo...

متن کامل

Pole-Balancing with Different Evolved Neurocontrollers

The paper presents various evolved neurocontrollers for the pole-balancing problem with good benchmark performance. They are small neural networks with recurrent connectivity. The applied evolutionary algorithm, which is not based on genetic algorithms, was designed to evolve neural networks with arbitrary connectivity. It uses no quantization of inputs, outputs or internal parameters, and sets...

متن کامل

Pole-balancing with Diierent Evolved Neurocontrollers ?

The paper presents various evolved neurocontrollers for the pole-balancing problem with good benchmark performance. They are small neural networks with recurrent connectivity. The applied evolutionary algorithm, which is not based on genetic algorithms, was designed to evolve neural networks with arbitrary connectivity. It uses no quantiza-tion of inputs, outputs or internal parameters, and set...

متن کامل

Evolving neurocontrollers for balancing an inverted pendulum.

This paper introduces an evolutionary algorithm that is tailored to generate recurrent neural networks functioning as nonlinear controllers. Network size and architecture, as well as network parameters like weights and bias terms, are developed simultaneously. There is no quantization of inputs, outputs or internal parameters. Different kinds of evolved networks are presented that solve the pol...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003