Abstract
A new (post-Shannon) informational approach is suggested in this paper, which allows to make deep analysis of nature of the information. It was found that information could be presented as an aggregate of quantitative (physical) and qualitative (structural) components to be considered together. It turned out that such full information theory could be efficiently used as the guiding theory at modeling of video-information recognition, perception and understanding. These hierarchical processes are solving the intellectual tasks step-by-step for formation of the corresponding video-information evaluation and also represent a strong interactions-measurements video-information’s ensuring adequacy of these assessments. That is why there is a need to build corresponding video information macro-objects (video-thesauruses) on every level of hierarchy of artificial vision system, which are formed by training (self-training) and form together an upward hierarchy of qualitative measuring scales. The top of this hierarchy is video-intelligence. Information theory of artificial intelligence is a logical development of new information approach from analysis to synthesis. Further “analysis through synthesis” allows establishing the informational nature and structure of not only video-intelligence, but also strong artificial intelligence, which for video-intelligence constitute as intellectual suprasystem.
Highlights
Intuitive representation of intelligence as some informational macro-object that a perform information processing for the purpose of her understanding led to deep revision of classical informational approach
This article discusses the development of post-Shannon informational approach, created at “NeocorTek Lab” where this approaches was adapted to the problem of videoinformation evaluation in artificial vision
2) The image forming process could be considered according to gauge theory as gauge transformation which is realized by means of the analysis of a weak video-information field representing a gauge field
Summary
Intuitive representation of intelligence as some informational macro-object that a perform information processing for the purpose of her understanding led to deep revision of classical (by Shannon) informational approach. As this approach was quite heuristic one, the goal was to build an overall view of surrounding material world properties using the actual advances in fundamental physics and mathematics without intuitive and heuristic aspects. The quantitative classical approach to information did not meet the needs of the researchers who deals with the tasks which qualitative nature became more obvious Such tasks as recognition, perception and understanding can be example. Any attempts to improve the classical informational approach by concept of information’s value and other intuitive and heuristic aspects did not lead to anything
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