Autonomous, Model-Based Diagnosis Agents (The Springer by Michael Schroeder

By Michael Schroeder

Autonomous, Model-Based prognosis Agents defines and describes the implementation of an structure for self sustaining, model-based prognosis brokers. It does this by means of constructing a good judgment programming strategy for model-based analysis and introducing ideas to house extra advanced analysis difficulties, after which embedding the analysis framework into the agent structure of bright brokers.
Autonomous, Model-Based prognosis Agents surveys prolonged good judgment programming and indicates how this expressive language is used to version analysis difficulties stemming from functions akin to electronic circuits, site visitors keep an eye on, integrity checking of a chemical database, alarm-correlation in mobile phone networks, analysis of an automated reflect furnace, and prognosis of conversation protocols. The publication studies a bottom-up set of rules to take away contradiction from prolonged common sense courses and considerably improves it by means of top-down overview of prolonged good judgment courses. either algorithms are evaluated within the circuit area together with many of the ISCAS85 benchmark circuits.
This accomplished in-depth research of ideas, architectures, and implementation of self sufficient, model-based prognosis brokers may be of nice price for researchers, engineers, and graduate scholars with a history in man made intelligence. For practitioners, it offers 3 major contributions: first, it offers many examples from different components corresponding to alarm correlation in mobilephone networks to inconsistency checking in databases; moment, it describes an structure to increase brokers; and 3rd, it describes a refined and declarative implementation of the suggestions and architectures introduced.

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