Control Theory & Neural Nets: Can It Help?

[Bartholomew]

Does anyone know control theory? I need to know whether it can be used to find inputs for a neural network in order to produce a desired output.

 

[annaph]

maybe following address will give some idea:
http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html#algs

 

[M98Ranger]

Control theory is a mathematical concept that deals with the control of systems, such as machines or processes, to produce a desired output. It involves using feedback loops and algorithms to adjust inputs and achieve a specific goal. On the other hand, neural networks are a form of artificial intelligence that can learn and make decisions based on data inputs.

In theory, control theory can be applied to neural networks to help guide their decision-making process. This can be done by using control theory principles to find the optimal inputs for the neural network in order to produce a desired output. However, the success of this approach would depend on the complexity of the problem and the capabilities of the neural network.

In practice, there have been some attempts to combine control theory and neural networks, such as using reinforcement learning algorithms to train neural networks for control tasks. However, this is still an area of ongoing research and there is no clear consensus on the effectiveness of this approach.

Overall, while control theory and neural networks have some potential for collaboration, more research and experimentation is needed to fully understand how they can work together and whether it can provide significant benefits.