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ESWATINI MEDICAL CHRISTIAN UNIVERSITY DEPARTMENT OF COMPUTER SCIENCE Course Code MCS 402 Tutorial ARTIFICIAL INTELLIGENCE Date 11 Nov 2019 Expert Systems a) What is the main purpose of Expert Systems? b) What is the main difference between conventional computer programs and production systems (rule based systems)? c) Why a production system model was used to implement the first rule based expert systems? d) What types of knowledge are used by neural networks and by rule based systems? e) What kinds of systems are they with respect to the type of knowledge they use? f) What are the main components of a rule based system? g) Why is knowledge acquisition often referred to as the ES `bottleneck'? Neural Network Logical operators (i.e. NOT, AND, OR, XOR, etc) are the building blocks of any computational device. Logical functions return only two possible values, true or false, based on the truth or false values of their arguments. For example, operator AND returns true only when all its arguments are true, otherwise (if any of the arguments is false) it returns false. If we denote truth by 1 and false by 0, then logical function AND can be represented by the following table: ๐ฅ1 ๐ฅ2 ๐ฅ1 ๐ด๐๐ท ๐ฅ2 0 0 0 1 0 0 0 1 0 1 1 1 This function can be implemented by a single unit with two inputs: if the weights are ๐ค1 = 1 and ๐ค2 = 1 and the activation function is: 1 ๐๐ ๐ฃ โฅ 2 ๐(๐ฃ) = { } 0 ๐๐กโ๐๐๐ค๐๐ ๐ Note that the threshold level is 2 (v โฅ2). a) Test how the neural AND function works. b) Suggest how to change either the weights or the threshold level of this single unit in order to implement the logical OR function (true when at least one of the arguments is true): ๐ฅ1 ๐ฅ2 ๐ฅ1 ๐๐ ๐ฅ2 0 0 0 1 0 1 0 1 1 1 1 1 c) The XOR function (exclusive or) returns true only when one of the arguments is true and another is false. Otherwise, it returns always false. This can be represented by the following table: ๐ฅ1 ๐ฅ2 ๐ฅ1 ๐๐๐ ๐ฅ2 0 0 0 1 0 1 0 1 1 1 1 0