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Autonomy Oriented Computing From Problem Solving to Complex by Jiming Liu, XiaoLong Jin, Kwok Ching Tsui

By Jiming Liu, XiaoLong Jin, Kwok Ching Tsui

AUTONOMY orientated COMPUTING is a accomplished reference for scientists, engineers, and different execs taken with this promising improvement in machine technology. it may possibly even be used as a textual content in graduate/undergraduate courses in a huge variety of computer-related disciplines, together with Robotics and Automation, Amorphous Computing, picture Processing, Programming Paradigms, Computational Biology, etc.
Part One describes the elemental strategies and features of an AOC method and enumerates the severe layout and engineering matters confronted in AOC method improvement. half provides specified analyses of methodologies and case experiences to judge AOC utilized in challenge fixing and complicated procedure modeling. the ultimate bankruptcy outlines probabilities for destiny examine and development.
Numerous illustrative examples, experimental case stories, and routines on the finish of every bankruptcy of AUTONOMY orientated COMPUTING support particularize and consolidate the methodologies and theories offered.

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

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In this sense, the environment can also be regarded as an indirect communication medium among entities. This is a dynamical view of the environment. For example, StarLogo [Resnick, 1994] has patches in the environment which knows how to grow food or evaporate ants’ pheromone. Sometimes the environment provides feedback to autonomous entities regarding their behavior. For example, in the n-queen constraint satisfaction problem, the environment can tell a queen how many constraints are violated in its neighborhood after it takes a move.

If AOC is used to solve a particular problem, the right level of abstraction has to be chosen so that autonomous entities can be identified. This does not exclude the repeated application of this technique to suit the need of the specific problem that can be best modeled by multiple levels of abstraction. Secondly, there are some relationships between autonomous entities in the form of constraints, such as limitations on the position inhabitable by a queen in an n-queen problem. Thirdly, a performance measurement is available to assess the quality of any solution.

Liu and Y. Y. Tang. Adaptive Segmentation with Distributed Behavior Based Agents. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(6):544-551, 1999. Any omission of credit or acknowledgement will be corrected in the future editions of this book. 1. Introduction Autonomy oriented computing (AOC) is a new bottom-up paradigm for problem solving and complex systems modeling. In this book, our goal is to substantiate this very statement and to demonstrate useful AOC methodologies and applications.

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