Artificial Intelligence .*;

Learning algorithms based on early neurological research.
Adaptive algorithms based on various evolutionary biology concepts.
Methods of finding efficient sequences.
Combinatorial solution finding based on metallurgical annealing concepts.
Methods of finding groups in data based on various relations.
Numeric optimization algorithms based on flocking and swarming patterns in nature.
A few tricks in creating logic for computer opponents.
modern computer circuitry often mirrors concepts in psychology and neurology

What Is Artificial Intelligence?

"This is no mad quest. Human brains don't work by magic, so whatever it is they do should be doable in suitably designed machines." --Dr. Aaron Sloman, University of Birmingham, United Kingdom.

It's often said in computer science that any problem without a linear solution is an "AI problem". We sometimes need algorithms that can adapt to unknown factors and noisy data.

The algorithms presented in this section are among my favorites.

To best understand how the algorithms work, it's best to study them in their simplest forms, and play around with them in code. I've posted simple demonstrations in common programming languages like C++, Java, Python, Javascript, Visual Basic, etc.

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