Fuzzy Thinking: The New Science of Fuzzy Logic – Bart Kosko – Google Books. Great entry point for the uninitiated with Fuzzy Logic concepts. Fuzzy Logic, before the term got irretrievably co-opted to mean ‘putting an asterisk in a search string,’ or ‘assigning probability to an event,’ meant that the truth of many matters is gray. May 20, 2010 - Aristotle is out and Buddha is in; the law of the excluded middle (either A or not-A) is repealed, and A and not-A together replaces it. No more black and white, right and wrong, true or false. In their place come shades of gray, more or less, maybe so, maybe not. Because the new world of fuzzy logic.
Contents. Personal background Kosko holds bachelor's degrees in philosophy and in economics from USC, a master's degree in applied mathematics from UC San Diego, a PhD in electrical engineering from UC Irvine, and an online J.D. In law from the online.
He is an attorney licensed in and federal court, and worked part-time as a for the 's Office. Kosko is a political and religious. He is a contributing editor of the periodical, where he has published essays on “Palestinian vouchers”. Writing Kosko’s most popular book to date was the international best-seller Fuzzy Thinking, about man and machines thinking in shades of gray, and his most recent book was Noise. He has also published and the cyber-thriller Nanotime, about a that takes place in two days of the year 2030. The novel’s title coins the term “nanotime” to describe the time speed-up that occurs when fast computer chips, rather than slow brains, house minds. Kosko has a minimalist prose style, not even using commas in his several books.
Research Kosko’s technical contributions have been in three main areas:, neural networks, and noise. In fuzzy logic, he introduced, fuzzy subsethood, additive fuzzy systems, fuzzy approximation theorems, optimal fuzzy rules, fuzzy associative memories, various neural-based adaptive fuzzy systems, ratio measures of fuzziness, the shape of fuzzy sets, the conditional variance of fuzzy systems, and the geometric view of (finite) fuzzy sets as points in hypercubes and its relationship to the ongoing debate of fuzziness versus. In neural networks, Kosko introduced the unsupervised technique of differential, sometimes called the “differential synapse,” and most famously the family of feedback neural architectures, with corresponding global stability theorems. In, Kosko introduced the concept of adaptive, using neural-like learning algorithms to find the optimal level of noise to add to many nonlinear systems to improve their performance. He proved many versions of the so-called “forbidden interval theorem,” which guarantees that noise will benefit a system if the average level of noise does not fall in an interval of values.
He also showed that noise can speed up the convergence of Markov chains to equilibrium. Books Nonfiction. Noise. Viking Press.
Intelligent Signal Processing. (with coauthor Simon Haykin). Heaven in a Chip: Fuzzy Visions of Society and Science in the Digital Age. Random House / Three Rivers Press. the Fuzzy Future: From Society and Science to Heaven in a Chip.
Random House / Harmony Books. Fuzzy Engineering. Prentice Hall.
Fuzzy Thinking: The New Science of Fuzzy Logic. Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice Hall. Neural Networks for Signal Processing. Prentice Hall. The Fuzzy Future: From society and science to heaven in a chip.
Fiction. Nanotime. References.
Fuzzy logic guru Bart Kosko explains Spock's worst nightmare. Bart Kosko holds degrees in philosophy, economics, math, and engineering. He chaired the first international conference on neural networks when he was 27. At 34, he is a tenured professor in electrical engineering at the University of Southern California. Kosko came to USC from the farmlands of Kansas on a full music scholarship - he wrote his first symphony when he was 18. Now he directs the prestigious Signal and Image Processing Institute, where he works on HDTV, brain scanning, and future effects for 'digital film.'
Kosko has written three textbooks and the best-selling Fuzzy Thinking. Today, you can find him pumping iron, scuba diving against the downward currents off the coast of Cozumel, or, armed with a bow-and-arrow, hunting wild boar. He recently shared a cigar with Sheldon Teitelbaum, filling a room with fuzzy ruminations. Wired: What is fuzzy logic and why do critics call it 'the cocaine of science?' Kosko: Fuzzy logic is Spock's worst nightmare - a way of doing science without math. It's a new branch of machine intelligence that tries to make computers think the way people think and not the other way around.
You don't write equations for how to wash clothes. Instead you load a chip with vague rules like 'if the wash water is dirty, add more soap,' and 'if very dirty, add a lot more.' All wash water is dirty and not dirty - to some degree.
It's just common sense. But it breaks the old either/or logic of Aristotle. That offends some scientists, who would like us to think and talk like off/on switches. But they still haven't produced a statement of fact like 'the sky is blue' or 'E=mc^2' that is 100 percent true or 100 percent false. Fact ain't math. You can never get the science right to more than a few decimal places.
That's one reason we find chaos when we look at things up close. Fuzzy systems are universal computers. I proved that as a theorem - the fuzzy approximation theorem. In theory, you can replace every book on physics or economics with equivalent books that have fuzzy systems where the equations used to be. Fuzzy systems are 'model-free' estimators. You don't have to guess at equations to build a bridge from inputs to outputs. Fuzzy rules build that bridge for you.
There is math behind the rules, but you don't need to know it to program a fuzzy system. You can program it in English. 'If the air is cool, turn the AC down a little.'
Fuzzy Thinking Bart Kosko
But the math is not fuzzy. That's why you can capture fuzzy logic in a digital chip. Most of the first fuzzy systems were in control - as in adjusting a camera lens or backing up a trailer truck to a loading dock. Now we're applying fuzzy systems to wireless communications and multimedia. The fuzzy rules can 'randomly' spread signals over a wide bandwidth or teach an intelligent agent the kind of houses or sunsets you prefer.
The math says we can apply them anywhere. In practice, it may not be so easy.
How can a fuzzy system screw up? The first problem is, where do you get them? Dumb rules give dumb systems. The bigger problem is rule explosion.
You want to add more variables to capture more causes and to make the system more realistic. You might add humidity and light intensity to temperature in the air conditioner. The catch is that the number of rules grows exponentially as you add new variables. So you try to find optimal rules. The math tells us they cover the turning points of the system - they patch the bumps.
Where do neural networks come in? At the front end. They tune the fuzzy rules by tuning the fuzzy concepts or sets. I may draw cool air as a triangle centered at 65 degrees Fahrenheit.
The air is 100 percent cool at 65 but only 80 percent cool at 63 or 67. You may draw a fatter or a thinner triangle. Or you may center it at 70. This reminds us that we don't all mean the same thing for even the most basic sensory terms. And that's OK. You get user friendliness by finding your own niche in the conceptual anarchy. You once consulted on the Tomahawk cruise missile.
What joys will fuzziness deliver in the way of ballistic buggery? The Smart War - all of our smart weapons against all of theirs. Right now, you have to store 50,000 to 100,000 images of a tank in a cruise missile's chip brain for a neural net to match against. Then it can tell a tank from a tree at all angles and resolutions. As chips continue to shrink, you can store more and more of these fuzzy patterns and allow the missile to reason with more and more fuzzy rules.
You are a well-published libertarian. Is there a political tie to fuzz? For me there are two. First, I am pro-choice on all issues.
Tyranny is one choice. Binary is next with two choices. Fuzz gives a whole spectrum of choices - and thus freedom of response. The pro-life zealot who wants to draw a hard line between life and death at conception or the first trimester is a binary tyrant of sorts.
There is no hard line between life and death. It's a curve, or fuzzy set. Second, I think someday we will see what I call a fuzzy tax form. As it works today, all your tax dollars go to general revenues. But suppose only half did, and the other half goes to social categories of your choice. Maybe 30 percent for AIDS research, 40 percent for debt relief, and 30 percent for environmental cleanup. That way you could set up real research bounties.
Our binary tax forms deny us such a choice. Taxes and death. You oppose them both. It's a hell of a thing to live in a machine that has no backup. I am one of 500 or so who has a cryonic bracelet and hopes to see if future nanotech can rebuild those cells and synapses. That, too, is a form of backup.
The better thing is just to upload in a chip. The brain stores about a billion billion bits of information and runs at about 10 million billion bits per second. Today you would need a chip the size of a house. But if Moore's Law keeps doubling the circuit density of chips every two years or so, by around 2020, your brain should fit to the last bit on a chip the size of a sugar cube.
You could last until your last chip fell into a black hole or star. On chip time, that may be as close to eternity as we can come in a universe made of matter and energy. Heaven or hell in a chip. Until then, it's burn, bury, or freeze. I wouldn't bet my life on cryonics, but I am happy to bet my death on it.