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Baby Steps into Genetic Programming
Table of Contents - 1 Introduction - 2 Generating Random Code - 3 Running Generated Code - 4 Population - 5 Fitness - 6 Generation Functions - 7 Advancing a Generation - 8 Conclusion - 9 Thanks 1 Introduction While my final ranking in the Google AI Contest was disappointing (280th), it was a very educational experience and was totally offset by Gábor Melis' dominating win using Common Lisp as well. One of things that piqued my interest during the contest was a post on the AI Challenge forums about a bot written using genetic programming.
We need a way to test the output of a generated function against our desired outcome and represent this as a number: the fitness. We also need to check whether the return value of RUN-FORM is NIL in which case it executed illegal code. The TEST-INPUT argument is a list of input values so the most direct approach will be to iterate over these values and running both the form and the fitness functions against them.
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