Genetic Algorithms And Evolutionary Learning .*;
- Example 1: Random Selection
- Example 2: Mutation
- Example 3: Shake Up Function Added In
- Example 4: Multiple Features
Simple Math Function Examples
These examples use genetic algorithms to evolve a combination of five numbers and four operators to create a simple expression that evaluates to a target answer.
For instance, we choose any five numbers between 0 and 9, then we choose four math operators from { +, -, *, / }. The goal is to create an expression that evaluates to a target value like 100. Evaluation goes from left to right. Something like this: 4 + 7 + 6 * 6 - 2 = 100
There are numerous combinations that can evaluate to 100, and these algorithms just need to come up with one.
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