By Jiming Liu
Autonomy orientated Computing is a accomplished reference for scientists, engineers, and different pros interested by this promising improvement in machine technological know-how. it will possibly even be used as a textual content in graduate/undergraduate courses in a vast variety of computer-related disciplines, together with Robotics and Automation, Amorphous Computing, picture Processing, Programming Paradigms, Computational Biology, and so on.
Part One describes the fundamental techniques and features of an AOC approach and enumerates the serious layout and engineering concerns confronted in AOC approach improvement. half offers specific analyses of methodologies and case reviews to judge AOC utilized in challenge fixing and intricate method modeling. the ultimate bankruptcy outlines probabilities for destiny examine and development.
Numerous illustrative examples, experimental case experiences, and workouts 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
An entity in AOC does not have mental parameters as in AOP. 2 AUTONOMY ORIENTED COMPUTING Computational Methodologies Now let us examine the computational philosophies of different paradigms. In both OOP and AOP, computation is embodied as a process of message passing and response among objects or agents. In AOP, computation involves certain techniques from Artificial Intelligence, such as knowledge representation, inference, and reasoning mechanisms. , transport scheduling) [Kuhnel, 1997]. In AOC, computation is carried out through the self-organization of autonomous entities.
The third phase, performance measurement, concerns the evaluation criteria for comparing the artificial system manifested by an AOC system with its natural counterpart. The measurement provides an indication to modify the current set of individual behaviors and behavioral rules. The end of this phase triggers the next cycle of the AOC modeling, if necessary, and involves modifications to some or all AOC elements defined in the previous cycle. 4. Engineering Issues The above mentioned three phases can be implemented with varying degrees of human involvement, from detailed engineering work to an automated process, leading to AOC systems capable of achieving various problem solving and systems modeling objectives.
The functional paradigm views computation as a process for evaluating a group of mathematical functions. In contrast to the imperative paradigm, it emphasizes the evaluation of functional expressions rather than the execution of commands. Both the imperative and the functional paradigms are to implement a mapping between inputs and outputs. The logic paradigm is to implement a general relation. It describes a set of features that a solution should have rather than a set of steps to obtain such a solution.