By Alex M. Andrew
The relative failure of makes an attempt to investigate and version intelligence might be attributed partially to the widespread assumption that the processing of constant variables and the manipulation of discrete options may be taken care of individually. during this ebook, the writer considers concept-based idea as having developed from processing of continuing variables. even though "fuzzy" concept recognizes the necessity to mix conceptual and non-stop processing, its assumption of the primacy of concept-based processing makes it evolutionarily implausible.
The textual content starts off by means of reviewing the origins and goals of cybernetics with specific connection with Warren McCulloch’s declared lifetime quest of "understanding man’s understanding". it's proven that non-stop structures can suffer advanced self-organization, yet a necessity for category of events turns into obvious and will be visible because the evolutionary starting of concept-based processing. percentages for complicated self-organization are emphasised by means of dialogue of a normal precept that has been termed value suggestions, of which backpropagation of blunders in neural nets is a unique case.
It is usually famous that non-stop measures turn out to be linked to processing that's basically concept-based, as stated in Marvin Minsky’s connection with heuristic connection among difficulties, and the linked simple studying heuristic of Minsky and Selfridge. This reappearance of continuity, besides observations at the multi-layer constitution of clever structures, helps a in all likelihood invaluable view of intelligence as having a fractal nature. this can be such that constructions at a fancy point, interpreted by way of those emergent measures, mirror others at a less complicated point. Implications for neuroscience and synthetic Intelligence also are examined.
The e-book offers unconventional and not easy viewpoints that might be of curiosity to researchers in AI, psychology, cybernetics and structures technology, and will support advertise additional research.
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Additional resources for A Missing Link in Cybernetics: Logic and Continuity
27 Fig. 1 Process with adaptive controller which a point represents the state of the process (insofar as it is monitored by these transducers) is divided into rectangular “boxes” within each of which all points are equivalent as far as control action is concerned. There will usually be a large loss of information in going from the continuous to the discrete representation, but this may be acceptable. Michie and Chambers (1967) developed a system they called BOXES to explore adaptive control. One of the applications they described was learning to play noughts-and-crosses (tic-tac-toe) by machine, though because this operates in a discrete environment, the special feature of division of a continuous representation space into “boxes” was not involved.
It does not, however, follow that discrete operation should play a part from the start. According to the viewpoint that will be developed here, attention should first be given to continuous control, from which classification and concept-based processing can emerge. An adaptive controller applied to a continuous industrial process is shown in Fig. 1. The controller receives signals a, b, and c from transducers in the process plant and generates control signals d and e. Associated with the controller is a means of evaluating the degree of goal achievement, normally an estimate of profit for an industrial process though other considerations might also enter.
There is a connection with the emphasis on the “fabric” of computing by Beer (1959), which will be referred to again in the next chapter. When McCulloch and Pitts (1943) produced the famous theory, they were well aware that their model neurons were unrealistic in many respects. One is that real neurons usually fire repetitively in a way that suggests the significant feature is the frequency and hence a continuous signal. It was argued, very reasonably, that it would be instructive to see what could be achieved with these highly simplified models of neurons, but reservations about the correspondence to real neural nets have often been ignored.
A Missing Link in Cybernetics: Logic and Continuity by Alex M. Andrew