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CS607 – Artificial Intelligence

In CS607 Artificial Intelligence we have you covered with Digitized Past Papers From Fall of Mid Term and Final Term.

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FINAL TERM

CS607 Final MCQs With Refrence Solved By Jahanzaib                 View     Download

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MID TERM

CS607 – Midterm Solved Mcqs references by Moaaz                          View     Download

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CS607 – SOLVED CURRENT MID PAPER Jahanzaib                         View     Download

POSTED DATE: 07-02-2019                        GDB IDEA SOLUTION

Conventional Programming vs. knowledge engineering Conventional programming is a sequential, three-step process: Design, Code, Debug. Knowledge engineering, which is the process of building an expert system, also involves assessment, knowledge acquisition, design, testing, documentation, and maintenance. However, there are some key differences between the two programming paradigms. Conventional programming focuses on a solution, while ES programming focuses on the problem. An ES is designed on the philosophy that if we have the right knowledge base, the solution will be derived from that data using a generic reasoning mechanism. Unlike traditional programs, you don’t just program an ES and consider it ‘built’. It grows as you add new knowledge. Once the framework is made, the addition of knowledge dictates the growth of ES.

1 Comment

  1. AYESHA MUMTAZ

    1- Advantages of neural network
    Answer:- (Page 187)
    • Excellent for pattern recognition
    • Excellent classifiers
    • Handles noisy data well
    • Good for generalization
    2- what is the difference between knowledge analysis and evaluation function
    Answer:- (Page 79 & 131)
    An evaluation function is the criteria that check various individuals/ solutions for being better than others
    in the population. Notice that mutation can be as simple as just flipping a bit at random or any number of
    bits.
    The goal of knowledge analysis is to analyze and structure the knowledge gained during the knowledge
    acquisition phase.
    3- Stages of life cycle of ESDLC
    Answer:- Rep
    4- steps of knowledge elicitation
    5- FIS applications
    Answer:- (Page 153)
    Fuzzy inference system (FIS) is the process of formulating the mapping from a given input to an output
    using fuzzy logic. This mapping then provides a basis from which decisions can be made, or patterns
    discerned
    Fuzzy inference systems have been successfully applied in fields such as automatic control, data
    classification, decision analysis, expert systems, and computer vision. Because of its multidisciplinary
    nature, fuzzy inference systems are associated with a number of names, such as fuzzy-rule-based
    systems, fuzzy expert systems, fuzzy modeling, fuzzy associative memory, fuzzy logic controllers, and
    simply (and ambiguously !!) fuzzy systems. Since the terms used to describe the various parts of the
    fuzzy inference process are far from standard, we will try to be as clear as possible about the different
    terms introduced in this section.
    6- Difference between supervised and unsupervised learning
    Answer:- Rep
    8- CNF conversion
    Answer:- (Page 107)
    Resolution requires all sentences to be converted into a special form called conjunctive normal form
    (CNF). A statement in conjunctive normal form (CNF) consists of ANDs of Ors.

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