LISP – (LISt Processing) 1. Parenthesized prefix notation: (+ 2 4) 2. Expressions can be nested: (- (+ 2 3 4 5) (* 2 5)) 3. Evaluation rule: apply function to value of arguments. 4. Symbolic computation: other types Primitive: numbers, characters, strings, symbols. Compound: lists. (append '(a b) '(c d)) --> (a b c d) Quote: block the evaluation of the following expression. '(a b) --> (a b) (a b) --> error: a undefined function. 5. Self-evaluating types: numbers, characters, strings. 6. Symbols as variables - not case sensitive. Quote append
VARIABLES 1. Define new objects in terms of others + name them. 2. (setf p '(a b)) --> (a b) p --> (a b) 3. Symbols also used to name functions. Quote
SPECIAL FORMS: 1. Forms not evaluated according to the evaluation rule. 2. Special forms: defun, defparameter, setf, let, case, if, function, quote.
LISTS 1. Primitive aggregating type. 2. Primitive functions: first, second, ..., length, last. append, cons, list.
DEFINING NEW FUNCTIONS: 1. (defun <name> (<parameters>) "doc" <body>) (defun last-name (name) "Select last name from a name represented as a list." (first (last name))) (last-name '(john r vandamme)) --> vandamme (last-name '(john quirk MD)) --> MD 2. Importance of abstraction. (defun first-name (name) (first name)) defun
USING FUNCTIONS: defparameter 1. (setf names '((john x ford) (peter p rabbit) (fabianna f wayne))) (mapcar #'last-name names) --> (ford rabbit wayne) #' from name of function to function object. mapcar primitive. 2. (defparameter *titles* '(Mr Mrs Miss Madam Ms Sir Dr Admiral Major General)) (defun first-name (name) "Select first name from a list representing a name." (if (member (first name) *titles*) (first-name (rest name)) (first name))) (if <test> <then-part> <else-part>) ;; explanation of if ;; example of first-name (first-name '(Madam Major General Paula Jones)) --> Paula 3. Trace functions defparameter Omits all titles from the name list, returns the first name.
HIGHER ORDER FUNCTIONS 1. Functions as first-class objects: can be manipulated, created, modified by running code. 2.Apply: (apply #'+ '(1 2 3 4)) --> 10 3. Funcall: (funcall #'+ 1 2) --> 3 (funcall #'+ '(1 2)) --> error (1 2) is not a number. 4. Function constructor: lambda. (lambda (parameter ...) body...): non atomic name of a function. ((lambda (x) (+ x 2)) 4) --> 6 (funcall #'(lambda (x) (* x 2)) 4) --> 8 ***Can create functions at run time.*** apply funcall lambda
OTHER DATA TYPES length 1. Strings: (length "abc") --> 3 2. Many number types. length
Basic terminology Atoms: word-like indivisible objects which can be numbers or symbols. Lists: sentence-like objects formed from atoms or other lists, and enclosed in parentheses. S-expressions: compositions of atoms and lists. Procedures: step by step specifications how to do something. Primitives: procedures supplied by the LISP itself Example: (+ 5 6) User-defined procedures: procedures introduced by the programmer. Example: (students 'anna) Program: a collection of procedures working together.
S-expressions An s-expression can have other s-expressions nested in it. Examples: (+ (* 5 7) ( / 2 4)) (This (is a dog) (or a cat)) Expressions can be interpreted both, procedurally and declaratively. If interpreted procedurally, an expression provides a direction for doing something. Such an expression is called a form, and its first element is the name of a procedure to be used to produce the value. The process of computing the value of an expression is called evaluation. If interpreted declaratively, expressions represent data. Data and procedures have the same syntax.
Evaluation of atoms The value of a number is the number itself. Example: 5 ==> 5 The value of a string is the string itself. Example: “Nice day” ==> “Nice day” The value of the symbol T is T (true). The value of the symbol NIL is NIL (false). The symbol NIL and the empty list ( ) are the same thing. Variables are names of memory locations. The contents stored in a given memory cell is the value of the variable serving as a name of this location. Example: Let x be a variable, and 5 be the contents of the memory cell called x. Then, the value of x is 5.
Numbers Integers: 179, 45 Ratio: 5/7, 7/9 Floating point: 5.2, 7.9 Examples: * (/ 25 5) 5 * (/ 46 9) 46/9 ; do not divide evenly * (float (/ 46 9)) 5.111111 * (round (/ 46 9)) 5 ; the nearest integer 1/9 ; the remainder
More numeric primitives * (- 6) -6 * (- -6) 6 * (max 5 7 2) 7 * (min 5 7 2) 2 * (sqrt (* (+ 1 3) (* 2 2))) 4.0 * (+ (round (/ 22 7)) (round (/ 7 3))) 5 * (+ 2 2.5) 4.5 * (expt 3 6) 729 * (sqrt 81) 9.0 * (sqrt 82) 9.055386 * (abs 6) 6 * (abs -6)
LISP EVALUATION RULE 1. Every expression is either a list or an atom. 2. Every list to be evaluated is either a special form or a function application. 3. A special form expression is a list whose first element is a special form operator and is evaluated according to the special rule of that operator. 4. A function application is evaluated by first evaluating the arguments (the rest of the list) and then finding the function named by the first element of the list and applying it to the list of evaluated arguments. 5. Every atom is either a symbol or a non-symbol. 6. A symbol evaluates to the most recent value assigned to the variable. 7. A non-symbol atom evaluates to itself.
WHAT MAKES LISP DIFFERENT 1. Built-in support for Lists. 2. Automatic memory management. 3. Dynamic typing. 4. First-class functions. 5. Uniform syntax. 6. Extensibility
Why LISP? Especially designed for symbol manipulation. Provides built-in support for lists (“everything is a list..”) Automatic storage management (no need to keep track of memory allocation). Interactive environment, which allows programs to be developed step by step. That is, if a change is to be introduced, only changed functions need to be recompiled.
Everything's a List! (a b c) (defun plus (x y) (+ x y)) Data Functions Simple syntax: (function-name arg1 arg2 …) (defun plus (x y) (+ x y))
LISP is Interpreted and interactive USER(1): 12 12 USER(2): (+ 12 3) 15 USER(3): (setf Almost-age 31) 31 USER(4): Almost-age USER(5): 'Almost-age ALMOST-AGE USER(6):
Lisp is Symbolic Why do we care about symbols? Understand human cognition with a language like symbolic processing
Physical Symbol System Hypothesis "A physical symbol system has the necessary and sufficient means for general intelligent action." (Newell & Simon 1976) Physical symbol system Set of entities called symbols - physical patterns that can occur as components Expressions (or symbol structures) built of symbols
Lisp is Dynamic USER(1): (+ 1 2 3) 6 USER(2): (apply #'+ '(1 2 3)) 6 Functions are first-class objects Pass functions as arguments to other functions USER(1): (+ 1 2 3) 6 USER(2): (apply #'+ '(1 2 3)) 6
Funcall and Lambda – dynamic Create functions on the fly Lisp contains itself: eval USER(1): (funcall #'(lambda (x y) (+ x y)) 17 14) 31
Name Calling Lisp remembers function names separately from variable names USER(22): (defun add (x y) (+ x y)) ADD USER(23): (setf add 9) 9 USER(24): add 9 USER(25): #'add #<Interpreted Function ADD>
Problems with solutions: Write a function (power 3 2) = 3^2 = 9 2. Write a function that counts the number of atoms in an expression. (count-atoms '(a (b) c)) --> 3 3. (count-anywhere 'a '(a ((a) b) a)) --> 3 4. (dot-product '(10 20) '(3 4)) --> 10x3 + 20x4 = 110 5. Write a function (flatten '(a (b) () ((c)))) --> (a b c) which removes all levels of parenthesis and returns a flat list of atoms. 6. Write a function (remove-dups '(a 1 1 a b 2 b)) --> (a 1 b 2) which removes all duplicate atoms from a flat list. (Note: there is a built-in remove-duplicates in Common Lisp, do not use it).
Solutions 1-3 Write a function (power 3 2) = 3^2 = 9 (defun power (a b) "compute a^b - (power 3 2) ==> 9" (if (= b 0) 1 (* a (power a (- b 1))))) (defun count-atoms (exp) "count atoms in expresion - (count-atoms '(a (b) c)) ==> 3" (cond ((null exp) 0) ((atom exp) 1) (t (+ (count-atoms (first exp)) (count-atoms (rest exp)))))) (defun count-anywhere (a exp) "count performances of a in expresion - (count-anywhere 'a '(a ((a) b) (a))) ==> 3" ((atom exp) (if (eq a exp) 1 0)) (t (+ (count-anywhere a (first exp)) (count-anywhere a (rest exp)))))) Write a function that counts the number of atoms in an expression. (count-atoms '(a (b) c)) --> 3 (count-anywhere 'a '(a ((a) b) a)) --> 3
Solutions (defun flatten (exp) Write a function (flatten '(a (b) () ((c)))) --> (a b c) which removes all levels of parenthesis and returns a flat list of atoms. (defun flatten (exp) "removes all levels of paranthesis and returns flat list of atoms (flatten '(a (b) () ((c)))) ==> (a b c)" (cond ((null exp) nil) ((atom exp) (list exp)) (t (append (flatten (first exp)) (flatten (rest exp))))))
A tree structure of nodes for data base EXAMPLE A tree structure of nodes for data base
Example of interaction with the program that will be shown: You type How it works? You have some item in mind, program asks, you respond. (questions) Is it a ANIMAL? (yes) Is it a MAMMAL? (yes) I give up - what is it? (whale) #S( NODE :NAME WHALE :YES NIL :NO NIL ) Is it a ANIMAL? (no) Is it a VEGETABLE? (no) Is it a MINERAL? (no) I give up - what is it? (fruit) #S( NODE :NAME FRUIT :YES NIL :NO NIL ) Is it a FRUIT? (it) AHA! Program responds Program learned this. Now it knows that whale is a mammal. You confirm that the program guessed correctly Program learned this. Now it knows that it is a fruit
e.g. 3: A tree structure of nodes for data base A data base called *db*. The data base is organized into a tree structure of nodes. Each node has three fields: the name of the object it represents, a node to go to if the answer is yes, and a node for when the answer is no. We traverse the nodes until we either get an “it” reply or have to give up. “It” means that we found a correct answer in our questioning. (defstruct node name (yes nil) (no nil)) NODE (defvar *db* (make-node :name 'animal :yes (make-node :name 'mammal) :no (make-node :name 'vegetable :no (make-node :name 'mineral)))) *DB* animal yes no mammal vegetable no node-name mineral node-yes node-yes node-no
Makes new node in the tree (defun give-up () (format t "~&I give up - what is it?") (make-node :name (first (read)))) GIVE-UP (defun questions (&optional (node *db*)) (format t "~&Is it a ~a? " (node-name node)) (case (first (read)) ((y yes) (if (not (null (node-yes node))) (questions (node-yes node)) (setf (node-yes node) (give-up)))) ((n no) (if (not (null (node-no node))) (questions (node-no node)) (setf (node-no node) (give-up)))) (it 'aha!) (t (format t "reply with YES, NO, or IT if I have guessed it.") (questions node)))) QUESTIONS Makes new node in the tree Returns name of function as a value Calls itself recursively Sets structure
Execution results: animal no yes mammal vegetable yes no whale yes (questions) Is it a ANIMAL? (yes) Is it a MAMMAL? (yes) I give up - what is it? (whale) #S( NODE :NAME WHALE :YES NIL :NO NIL ) Is it a ANIMAL? (no) Is it a VEGETABLE? (no) Is it a MINERAL? (no) I give up - what is it? (fruit) #S( NODE :NAME FRUIT :YES NIL :NO NIL ) Is it a FRUIT? (it) AHA! animal yes no mammal vegetable yes no whale yes mineral fruit IT!
A simple lisp program of generating English sentences EXAMPLE: A simple lisp program of generating English sentences
e.g. 4: A simple lisp program of generating English sentences (defun random-elt (choices) "Choose an element from a list at random" (elt choices (random (length choices)))) RANDOM-ELT (defun one-of (set) "pick one element of set and make a list of it" (list (random-elt set))) ONE-OF (defun Verb () (one-of '(hit took saw liked))) VERB (defun Noun () (one-of '(man ball woman table))) NOUN (defun Article () (one-of '(the a))) ARTICLE
Pictures drawn by a robot Dances Music composed (defun verb-phrase () (append (Verb) (noun-phrase) )) VERB-PHRASE (defun noun-phrase () (append (Article) (Noun))) NOUN-PHRASE (defun sentence () (append (noun-phrase ) (verb-phrase))) SENTENCE (sentence) (THE MAN SAW THE TABLE) (A TABLE SAW THE BALL) (A MAN SAW THE BALL) Similarly, you can create “sentences” in any kind of “structured” set, which is a language: Motions Facial gestures Pictures drawn by a robot Dances Music composed
A rule-based solution of generating English sentences EXAMPLE: A rule-based solution of generating English sentences
e.g. 5: A rule-based solution of generating English sentences (defparameter *simple-grammar* '((sentence -> (noun-phrase verb-phrase)) (noun-phrase -> (ar Noun)) (verb-phrase -> (Verb noun-phrase)) (ar -> the a) (Noun -> man ball woman table) (Verb -> hit took saw liked)) "A grammar for a trivial subset of English.") *SIMPLE-GRAMMAR* (defvar *grammar* *simple-grammar* "The grammar used by generate. Initially, this is *simple-grammar*, but we can switch to other grammars.") *GRAMMAR* (defun rule-lhs (rule) "The left-hand side of a rule" (first rule)) RULE-LHS
(defun rule-rhs (rule) "The right-hand side of a rule" (rest (rest rule))) RULE-RHS (defun rewrite(category) "return a list of the possible rewritees for this category" (rule-rhs (assoc category *grammar*))) REWRITE (defun random-elt (choices) "choose an element from a list at random" (elt choices (random (length choices)))) RANDOM-ELT (defun mappend (fn the-list) "Apply fn to each element of list and append the result" (apply #'append (mapcar fn the-list))) MAPPEND
(defun generate (phrase) "Generate a random sentence or a phrase" (cond ((listp phrase) (mappend #'generate phrase)) ((rewrite phrase) (generate (random-elt (rewrite phrase)))) (t (list phrase)))) GENERATE (generate 'sentence) (THE WOMAN LIKED A TABLE) (generate 'noun-phrase) (A WOMAN) (generate 'verb-phrase) (TOOK A WOMAN) (generate 'Verb) (HIT) (generate 'Noun) (BALL) (generate 'Article) (THE)
Exercise Problems If you have time, try to do the following exercise problems. Modify e.g.3 and make a data base of English words: verb (intransitive verb, transitive verb), noun, article, adjective, adverb, preposition, …, etc. Write a version of generate function that explicitly differentiates between terminal symbols (those with no rewrite rules) and non terminal symbols. Defining a new grammar that includes adjectives, prepositional phrases, proper names, and pronouns.
Simple Lisp Programs AI: Exercise 5 References: http://www-itolab.ics.nitech.ac.jp/LISP/text-contents.html http://grimpeur.tamu.edu/~colin/lp/lp.html http://www-2.cs.cmu.edu/Groups/AI/html/cltl/clm/#R http://www.cs.utsa.edu/research/AI/cltl/clm/clm.html
http://clisp.cons.org/ http://sourceforge.net/projects/clisp