Jiming Liu's Autonomy Oriented Computing From Problem Solving to Complex PDF

By Jiming Liu

Autonomy orientated Computing is a complete reference for scientists, engineers, and different pros excited by this promising improvement in desktop technology. it could possibly even be used as a textual content in graduate/undergraduate courses in a large variety of computer-related disciplines, together with Robotics and Automation, Amorphous Computing, snapshot Processing, Programming Paradigms, Computational Biology, and so forth.

Part One describes the elemental suggestions and features of an AOC approach and enumerates the serious layout and engineering concerns confronted in AOC approach improvement. half supplies precise analyses of methodologies and case reviews to judge AOC utilized in challenge fixing and complicated approach modeling. the ultimate bankruptcy outlines percentages for destiny study and development.

Numerous illustrative examples, experimental case reviews, and routines on the finish of every bankruptcy of Autonomy orientated Computing support particularize and consolidate the methodologies and theories presented.

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Extra info for Autonomy Oriented Computing From Problem Solving to Complex Systems Modeling

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Nature is full of complex systems some of which have been extensively studied from different angles and with different objectives. Some researchers want to understand the working mechanism of a complex system concerned. , 2000]. Similarly, economists want to know the factors contributing to the ups and downs in share prices. The knowledge gained in this way helps scientists predict future systems behavior. Others studying complex systems behavior want to simulate the observed complex behavior and formulate problem solving strategies for hard computational problems, such as global optimization.

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. However, homogeneity can be at varying degrees at different parts of the image. This presents problems to conventional methods, such as split-andmerge that segments an image by iteratively partitioning heterogeneous regions and simultaneously merging homogeneous ones [Pavlidis, 1992, Pitas, 1993].

AUTONOMY ORIENTED COMPUTING 12 Another example of multi-entity computation is ecology of computation [Hogg and Huberman, 1993, Huberman, 1988], where a population of heterogeneous computational systems share partial solutions to a common problem at hand. These individual problem solvers tackle the problem with different methods and, therefore, have different internal representations of the problem and solution. While it has been shown that this approach is efficient in solving a problem, the coordination of problem solvers needs to be carefully articulated so that different internal representations can be properly translated.

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Autonomy Oriented Computing From Problem Solving to Complex Systems Modeling by Jiming Liu


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