How to Create a Mind: The Secret of Human Thought Revealed

by Ray Kurzweil

we determine a way to code possible solutions to a given problem. If the problem is optimizing the design parameters for a circuit, then we define a list of all of the parameters (with a specific number of bits assigned to each parameter) that characterize the circuit. This list is regarded as the genetic code in the genetic algorithm. Then we randomly generate thousands or more genetic codes. Each such genetic code (which represents one set of design parameters) is considered a simulated “solution” organism. Now we evaluate each simulated organism in a simulated environment by using a defined method to assess each set of parameters. This evaluation is a key to the success of a genetic algorithm. In our example, we would run each program generated by the parameters and judge it on appropriate criteria (did it complete the task, how long did it take, and so on). The best-solution organisms (the best designs) are allowed to survive, and the rest are eliminated. Now we cause each of the survivors to multiply themselves until they reach the same number of solution creatures. This is done by simulating sexual reproduction: In other words, we create new offspring where each new creature draws one part of its genetic code from one parent and another part from a second parent.