By John R. Koza, Martin A. Keane, Matthew J. Streeter, William Mydlowec, Jessen Yu, Guido Lanza
Genetic Programming IV: regimen Human-Competitive desktop Intelligence provides the appliance of GP to a wide selection of difficulties related to computerized synthesis of controllers, circuits, antennas, genetic networks, and metabolic pathways. The e-book describes fifteen cases the place GP has created an entity that both infringes or duplicates the performance of a formerly patented 20th-century invention, six situations the place it has performed an identical with appreciate to post-2000 patented innovations, situations the place GP has created a patentable new invention, and 13 different human-competitive effects. The publication also establishes:GP now supplies regimen human-competitive desktop intelligenceGP is an automatic invention machine.GP can create normal recommendations to difficulties within the kind of parameterized topologies.GP has brought qualitatively extra mammoth ends up in synchrony with the relentless new release of Moore's legislations
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Each amplifier contributed some small (say, 1%) distortion. Cascading a hundred of these things guaranteed that what came out didn’t very much resemble what went in. “The main ‘solution’ at the time was to (try to) guarantee ‘small signal’ operation of the amplifiers. That is, by restricting the dynamic range of the signals to a tiny fraction of the amplifier’s overall capability, more linear operation could be achieved. Unfortunately, this strategy is quite inefficient since it requires the construction of, say, 100-W amplifiers to process milliwatt signals.
In a circuit, the component types are usually transistors, resistors, and capacitors. In a controller, the components are integrators, differentiators, gain blocks, adders, subtractors, and the like. , the capacitance of a capacitor in a circuit, the amplification factor of a gain block in a controller). Some of these genetically created mathematical expressions contain free variables. The free variables confer generality on the genetically evolved solution by enabling a single genetically evolved graphical structure to represent a general (parameterized) solution to an entire category of problems.
Did the method top out at this stage? Has the method solved problems from multiple domains (or is it nicheware)? ● Are the domains difficult? ● Did the method top out at this stage? Were the results human-competitive? Can the method profitably take advantage of the increased computational power available by means of parallel processing (or is it serialware)? Or, is the method Mooreware—able to take advantage of the exponentially increasing computational power made available by the relentless iteration of Moore’s law?