< Artificial Intelligence

In my quest to construct a circit that mimics a neuron in the brain, I ended with a circuit that exhibitted the following results

There are two types of learning

  • Memorized learning
  • Algorithimization

Memorized learning

Lets take the case of Fibonacci series 0,1,1,2,3,5,8,13,21,34 .............. Say you want to train a circuit the when given a number n gives out the nth Fibonacci number. Example if given n=5 the circuit gives out 3 and so on. When we try to train the circuit by this way the circuit simply remembers that at n=0,1,2,3,4,5 and so on the output must be 0,1,1,2,3 etc.

Algorithmization

But instead if we train give a seed value of 0,1 and variable n which represents a feed back we can get a circuit that forms a algorithm that can generate Fibonacci series, rather than one that just remembers.

If a circuit undergoes algorithmized training it can generate output for previously encountered and non encountered values that are given as input. Else if a circit has learned by memorization it can give right output for previously trained values, but may give out erroneous output for previously nonencountered inputs.

This article is issued from Wikibooks. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.