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Additional resources for Autonomy Oriented Computing
What will be its constructs? What will be the key characteristics and requirements of its operations? 2 In order to evaluate computing languages or environments for AOC, what will be your suggested criteria? What will be your suggested benchmark problems? 3 AOC offers a new way of tackling complexity, whether in problem solving or in complex systems modeling, by utilizing localized, autonomous and yet low-cost (computationally and physically speaking), and self-organized entities. Based on the illustrative examples given in this chapter, try to suggest and develop some other alternative models of AOC, as inspired by nature, for solving the same or different problems.
Entities can recognize and distinguish feature locations, if encountered, and then decide and execute their reactive behavior. 1(a), and selects its behavior according to the concentration of elements in the neighboring region. If the concentration is within a certain range, the current location satisfies a triggering condition. This activates the reproduction mechanism of the entity. 1(b) and (c). 2 Image Segmentation Problem Image segmentation requires to identify homogeneous regions within an image.
An abstracted version of some natural phenomenon is the starting point of AOC so that the problem at hand can be recasted. AUTONOMY ORIENTED COMPUTING 8 Formulating an AOC system involves an appropriate analogy that normally comes from nature. Employing such an analogy requires identification, abstraction, and reproduction of a certain natural phenomenon. The process of abstraction inevitably involves certain simplification of the natural counterpart. For example, the commonly used version of the genetic algorithm [Holland, 1992] in the family of evolutionary algorithms simplifies the process of sexual evolution to selection, recombination, and mutation, without explicit identification of male and female.