Neural Networks For The PIC Microcontroller | Part 4 | Self-Organizing Maps
By
Heather Dewey-Hagborg
January 2008, Page 67
Imagine if your robot could learn to characterize its sensations. Could it evolve its own language to describe its “feelings?” They might be literal sensations derived from sensors rather than self-reflection, but it is still a provocative idea ...
Artificial Life | Part 1 | Introduction to Genetic Algorithms
By
Heather Dewey-Hagborg
March 2008, Page 67
Have you ever questioned the meaning of “life?” I’m not talking about existentialism here, but the meaning of the word — life — what it means to be alive? Have you ever wondered, for example, if there was some way, some possibility, that an electronic creation (your electronic creation) could one day be deemed alive?
Artificial Life | Part 2 | Genetic Algorithms: Hello World
By
Heather Dewey-Hagborg
May 2008, Page 68
Last time, we talked about the theory behind genetic algorithms and looked at an abstract example of how they work. In this month’s article, we will implement a simple example on the PIC to understand the details and difficulties of doing this kind of programming on such a limited processor...
Random Bits
By
Heather Dewey-Hagborg
July 2008, Page 67
Throughout this column, we have relied on the idea of randomness to seed all of our unconventional computing experiments. In this month’s article, we will take a brief detour from code and hardware to examine just what the concept of “random” actually means, how our microcontroller is implementing it, how this differs from a computer, and some schemes for creating “true” random number generators...
Artificial Life | Part 3 | Genetic Algorithms: Interactive Evolution
By
Heather Dewey-Hagborg
September 2008, Page 67
The mathematical possibilities are exciting, but Genetic Algorithms can also be beautiful and it is this artistic and aesthetic potential we will be exploring in this article.
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