By Luis Argüelles Mendez
This publication uses the LISP programming language to supply readers with the mandatory heritage to appreciate and use fuzzy good judgment to unravel basic to medium-complexity real-world difficulties. It introduces the fundamentals of LISP required to take advantage of a Fuzzy LISP programming toolbox, which was once in particular applied by means of the writer to “teach” the speculation in the back of fuzzy good judgment and whilst equip readers to exploit their newly-acquired wisdom to construct fuzzy types of accelerating complexity. The e-book fills a big hole within the literature, supplying readers with a practice-oriented reference consultant to fuzzy good judgment that provides extra complexity than renowned books but is extra available than different mathematical treatises at the subject. As such, scholars in first-year collage classes with a easy tertiary mathematical history and no earlier adventure with programming could be capable of simply stick to the content material. The ebook is meant for college kids and execs within the fields of computing device technological know-how and engineering, as good as disciplines together with astronomy, biology, medication and earth sciences. software program builders can also reap the benefits of this booklet, that's meant as either an introductory textbook and self-study reference advisor to fuzzy common sense and its functions. the whole set of services that make up the bushy LISP programming toolbox could be downloaded from a significant other book’s website.
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Additional info for A Practical Introduction to Fuzzy Logic using LISP
As we saw in Sect. 4, cons takes two arguments, but successive calls to cons causes a deepening of the formed list. As an example let us use cons by building a queue of cars at the toll facility: > (setq queue (cons ‘CKT8623 ’GWG2719)) : (CKT8623 GWG2719) > (setq queue (cons queue ‘MKA8772)) : ((CKT8623 GWG2719) MKA8772) > (setq queue (cons queue ‘DYN2140)) : (((CKT8623 GWG2719) MKA8772) DYN2140) Do you appreciate the problem with the function (cons) when used this way? 7 Rotate, Extend and Flat 45 By the way, have you noticed that the combination of the functions (cons) and (flat) are still another way to model a queue with FIFO discipline?
While we are speaking about roulettes, casinos and chance, it seems convenient to introduce the function random. This function simply returns a real number between 0 and 1 at random (strictly speaking no computer is able to generate pure random numbers, but the use of pseudo-random numbers is usually enough for representing random events in the real world). 283314746 In order to obtain a random integer number from 0 to 36 we should type: > (setq alpha (integer (mul (random) 37))) : 24 Now, we can give a spin with a value alpha to our roulette and obtain the ﬁrst element after the rotation of the roulette is applied: > (ﬁrst (rotate roulette alpha)) : 13 Now you can argue that a simple call to (mul (random) 37) could produce the same roulette simulation, and you are true, but our model not only gets a random number between 0 and 36 but it also models the position of the roulette wheel: > roulette : (13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 0 1 2 3 4 5 6 7 8 9 10 11 12) Another application for rotate could be to save a programming step in our example of toll station.
The name of every predicate always ends with a question mark. Let us type the following Lisp expressions with attention: > (atom? a) : true Since “a”, either containing a value or not, is indivisible, is clearly an atom. > (symbol? ‘a) : true Here “a” is quoted, that is, it is not evaluated by Lisp, so it is a completely legal symbol for Lisp. It does not matter if it holds any associated value. >a : nil The direct evaluation of “a” returns nil because it does not contains anything. We have not yet assigned any value to it by means of the function setq so Lisp evaluates it to nil.