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Prolog
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#+TITLE: Seven Languages in Seven Weeks
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#+BEAMER_HEADER: \subtitle{Prolog}
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#+BEAMER_HEADER: \institute[INST]{Extreme Tech Seminar}
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#+AUTHOR: Correl Roush
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#+EMAIL: correl@gmail.com
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#+DATE: June 24, 2015
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#+OPTIONS: H:2 toc:nil ^:nil
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#+STARTUP: beamer indent
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#+COLUMNS: %45ITEM %10BEAMER_env(Env) %10BEAMER_act(Act) %4BEAMER_col(Col) %8BEAMER_opt(Opt)
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#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.0 :ETC
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#+LaTeX_CLASS: beamer
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#+LaTeX_CLASS_OPTIONS: [presentation,aspectratio=169]
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* Introduction
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** Introduction
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*** Prolog :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.6
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:END:
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- Created :: 1972
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- Author :: Alain Colmerauer and Phillipe Roussel
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A declarative logic programming language.
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*** Rain Man :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.4
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:END:
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#+ATTR_LATEX: :width \textwidth
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[[file:rainman.jpg]]
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** Getting Prolog
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*** GNU Prolog
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http://www.gprolog.org/
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*** SWI Prolog
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http://www.swi-prolog.org/
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* Day 1
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** Day 1: An Excellent Driver
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- Atoms & Variables
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- Facts & Rules
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- Unification
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** Atoms & Variables
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*** Atoms
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- Begin with a lowercase letter.
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*** Variables
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- Begin with an uppercase letter.
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** Basic Facts & Queries
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*** Rules & Facts :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** Facts
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:PROPERTIES:
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:END:
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#+begin_src prolog
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likes(wallace, cheese).
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likes(grommit, cheese).
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likes(wendolene, sheep).
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#+end_src
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**** Rules
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:PROPERTIES:
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:END:
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#+begin_src prolog
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friend(X, Y) :- \+(X = Y),
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likes(X, Z),
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likes(Y, Z).
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#+end_src
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*** Queries :B_example:BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:BEAMER_env: example
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:END:
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#+begin_src prolog
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likes(wallace, sheep).
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%% false
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#+end_src
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#+begin_src prolog
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likes(grommit, cheese).
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%% true
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#+end_src
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#+begin_src prolog
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friend(grommit, wallace).
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%% true
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#+end_src
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#+begin_src prolog
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friend(wallace, grommit).
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%% true
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#+end_src
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#+begin_src prolog
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friend(wendolene, grommit).
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%% false
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#+end_src
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#+RESULTS:
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** Filling in the Blanks
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*** Food Facts :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** Facts
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#+begin_src prolog
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food_type(velveeta, cheese).
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food_type(ritz, cracker).
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food_type(spam, meat).
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food_type(sausage, meat).
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food_type(jolt, soda).
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food_type(twinkie, dessert).
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flavor(sweet, desert).
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flavor(savory, meat).
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flavor(savory, cheese).
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flavor(sweet, soda).
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#+end_src
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**** Rules
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#+begin_src prolog
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food_flavor(X, Y) :- food_type(X, Z),
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flavor(Y, Z).
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#+end_src
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*** Queries :B_example:BMCOL:
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:PROPERTIES:
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:BEAMER_env: example
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:BEAMER_col: 0.5
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:END:
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#+begin_src prolog
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food_type(What, meat).
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%% What = spam ;
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%% What = sausage.
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#+end_src
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#+begin_src prolog
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food_flavor(sausage, sweet).
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%% false.
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#+end_src
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#+begin_src prolog
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flavor(sweet, What).
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%% What = dessert ;
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%% What = soda.
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#+end_src
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#+begin_src prolog
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food_flavor(What, savory).
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%% What = velveeta ;
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%% What = spam ;
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%% What = sausage.
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#+end_src
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** Map Coloring: Problem
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*** Map :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.3
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:END:
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#+ATTR_LATEX: \textwidth
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[[file:prolog-map.png]]
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*** Problem :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.7
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:END:
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- We want to color a map of the southeastern United States.
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- We do not want two states of the same color to touch.
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- We will use three colors: red, blue, and green.
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** Map Coloring: Solution
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*** Map Facts :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** Facts
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#+begin_src prolog
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different(red, green). different(red, blue).
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different(green, red). different(green, blue).
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different(blue, red). different(blue, green).
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coloring(Alabama, Mississippi,
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Georgia, Tennessee, Florida) :-
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different(Mississippi, Tennessee),
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different(Mississippi, Alabama),
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different(Alabama, Tennessee),
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different(Alabama, Mississippi),
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different(Alabama, Georgia),
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different(Alabama, Florida),
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different(Georgia, Florida),
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different(Georgia, Tennessee).
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#+end_src
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*** Query :B_example:BMCOL:
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:PROPERTIES:
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:BEAMER_env: example
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:BEAMER_col: 0.5
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:END:
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#+begin_src prolog
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coloring(Alabama, Mississippi,
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Georgia, Tennessee, Florida).
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%% Alabama = blue,
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%% Florida = green,
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%% Georgia = red ,
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%% Mississippi = red,
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%% Tennessee = green ;
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#+end_src
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** Unification, Part 1
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*** Facts & Rules :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** Unification
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Unification across two structures tries to make both structures
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identical.
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**** Facts
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#+begin_src prolog
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cat(lion).
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cat(tiger).
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#+end_src
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**** Rules
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#+begin_src prolog
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dorothy(X, Y, Z) :- X = lion,
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Y = tiger,
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Z = bear.
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twin_cats(X, Y) :- cat(X), cat(Y).
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#+end_src
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*** Unification :B_example:BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:BEAMER_env: example
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:END:
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#+begin_src prolog
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dorothy(lion, tiger, bear).
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%% true.
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dorothy(One, Two, Three).
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%% One = lion,
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%% Two = tiger,
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%% Three = bear.
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twin_cats(One, Two).
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%% One = lion,
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%% Two = lion ;
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%% One = lion,
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%% Two = tiger ;
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%% One = tiger,
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%% Two = lion ;
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%% One = tiger,
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%% Two = tiger.
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#+end_src
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** Interview
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#+BEGIN_CENTER
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An interview with Brian Tarbox, Dolphin Researcher
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#+END_CENTER
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** Exercises
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#+BEGIN_CENTER
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EXERCISES
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#+END_CENTER
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* Day 2
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** Day 2: Fifteen Minutes to Wapner
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- Recursion
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- Lists and Tuples
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- Unification
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- Lists and Math
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- Using rules in Both Directions
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** Recursion
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The following rules define the paternal family tree of the Waltons.
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They express a father relationship and from that infers the ancestor
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relationship. Since an ancestor can mean a father, grandfather, or
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great grandfather, we will need to nest the rules or iterate.
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#+begin_src prolog
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father(zeb, john_boy_sr).
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father(john_boy_sr, john_boy_jr).
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ancestor(X, Y) :-
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father(X, Y).
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ancestor(X, Y) :-
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father(X, Z), ancestor(Z, Y).
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#+end_src
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||||
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In the above example, =ancestor(Z, Y)= is a *recursive subgoal*.
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** Lists and Tuples
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- Lists are containers of variable length.
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- Tuples are containers with a fixed length.
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** Unification, Part 2: Tuples
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Tuples unify if they have the same number of elements, and each
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element unifies.
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#+begin_src prolog
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(1, 2, 3) = (1, 2, 3). %% true
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(1, 2, 3) = (1, 2, 3, 4). %% false
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(1, 2, 3) = (3, 2, 1). %% false
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#+end_src
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** Unification, Part 2: Lists
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Lists behave similarly, but can be deconstructed with the pattern
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=[Head|Tail]=.
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#+begin_src prolog
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[1, 2, 3] = [1, 2, 3]. %% true
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[2, 2, 3] = [X, X, Z]. %% X = 2, Z = 3
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[a, b, c] = [Head|Tail]. %% Head = a, Tail = [b, c]
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[] = [Head|Tail]. %% false
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[a] = [Head|Tail]. %% Head = a, Tail = []
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[a, b, c] = [a|[Head|Tail]]. %% Head = b, Tail = [c]
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[a, b, c, d, e] = [_, _|[Head|_]]. %% Head = c
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#+end_src
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** Lists and Math
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*** Count
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#+begin_src prolog
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count(0, []).
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count(Count, [Head|Tail]) :- count(TailCount, Tail), Count is TailCount + 1.
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#+end_src
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*** Sum
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#+begin_src prolog
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sum(0, []).
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sum(Total, [Head|Tail]) :- sum(Sum, Tail), Total is Head + Sum.
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#+end_src
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*** Average
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#+begin_src prolog
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average(Average, List) :- sum(Sum, List), count(Count, List), Average is Sum/Count.
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#+end_src
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** Using Rules in Both Directions
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The rule =append(List1, List2, List3)= is true if =List3= is =List1= +
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=List2=.
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*** Left :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** ... as a lie detector
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#+begin_src prolog
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append([oil], [water],
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[oil, water]). %% true
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append([oil], [water],
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[oil, slick]). %% false
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#+end_src
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**** ... as a list builder
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#+begin_src prolog
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append([tiny], [bubbles],
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What).
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%% What = [tiny, bubbles]
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#+end_src
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*** Right :BMCOL:
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:PROPERTIES:
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:BEAMER_col: 0.5
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:END:
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**** ... for list subtraction
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#+begin_src prolog
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append([dessert_topping], Who,
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[dessert_topping, floor_wax]).
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%% Who = [floor_wax]
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#+end_src
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**** ... for computing possible splits
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#+begin_src prolog
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append(One, Two,
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[apples, oranges, bananas]).
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%% One = [], Two = [apples, oranges, bananas]
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%% One = [apples], Two = [oranges, bananas]
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%% One = [apples, oranges], Two = [bananas]
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%% One = [apples, oranges, bananas], Two = []
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#+end_src
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** Implementing append/3
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Steps:
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1. Write a rule called =concatenate(List1, List2, List3)= that can
|
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concatenate an empty list to =List1=.
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2. Add a rule that concatenates one item from =List1= onto =List2=.
|
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3. Add a rule that concatenates two and three items from =List1= onto
|
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=List2=.
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4. See what we can generalize.
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|
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** concatenate/3: Step 1
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=concatentate/3= is =true= if the first parameter is an empty list and
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the next two parameters are the same.
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|
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#+begin_src prolog
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concatenate([], List, List).
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#+end_src
|
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|
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*** Test :B_example:
|
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:PROPERTIES:
|
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:BEAMER_env: example
|
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:END:
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#+begin_src prolog
|
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concatenate([], [harry], What).
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%% What = [harry]
|
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#+end_src
|
||||
|
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** concatenate/3: Step 2
|
||||
Add a rule that concatenates the first element of =List1= tot he front
|
||||
of =List2=:
|
||||
|
||||
#+begin_src prolog
|
||||
concatenate([Head|[]], List, [Head|List]).
|
||||
#+end_src
|
||||
|
||||
*** Test :B_example:
|
||||
:PROPERTIES:
|
||||
:BEAMER_env: example
|
||||
:END:
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||||
#+begin_src prolog
|
||||
concatenate([malfoy], [potter], What).
|
||||
%% What = [malfoy, potter]
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||||
#+end_src
|
||||
|
||||
** concatenate/3: Step 3
|
||||
Define another couple of rules to concatenate lists of lengths 2 and
|
||||
3:
|
||||
|
||||
#+begin_src prolog
|
||||
concatenate([Head1|[Head2|[]]], List, [Head1, Head2|List]).
|
||||
concatenate([Head1|[Head2|[Head3|[]]]], List, [Head1, Head2, Head3|List])
|
||||
#+end_src
|
||||
|
||||
*** Test :B_example:
|
||||
:PROPERTIES:
|
||||
:BEAMER_env: example
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
concatenate([malfoy, granger], [potter], What).
|
||||
%% What = [malfoy, granger, potter]
|
||||
#+end_src
|
||||
|
||||
** concatenate/3: Step 4
|
||||
Generalize for lists of arbitrary length using nested rules:
|
||||
|
||||
#+begin_src prolog
|
||||
concatenate([], List, List).
|
||||
concatenate([Head|Tail1], List, [Head|Tail2]) :-
|
||||
concatenate(Tail1, List, Tail2).
|
||||
#+end_src
|
||||
|
||||
** Exercises
|
||||
#+BEGIN_CENTER
|
||||
EXERCISES
|
||||
#+END_CENTER
|
||||
|
||||
* Day 3
|
||||
|
||||
** Day 3: Blowing Up Vegas
|
||||
- Sudoku
|
||||
- Eight Queens
|
||||
** Solving Sudoku: The Problem
|
||||
- For a solved puzzle, the numbers in the puzzle and solution should
|
||||
be the same.
|
||||
- A Sudoku board is a grid of sixteen cells, with values from 1-4.
|
||||
- The board has four rows, four columns, and four squares.
|
||||
- A puzzle is valid if the elements in each row, column, and square
|
||||
has no repeated elements.
|
||||
|
||||
*** Example :B_example:
|
||||
:PROPERTIES:
|
||||
:BEAMER_env: example
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
sudoku([_, _, 2, 3,
|
||||
_, _, _, _,
|
||||
_, _, _, _,
|
||||
3, 4, _, _],
|
||||
Solution).
|
||||
#+end_src
|
||||
** Solving Sudoku: The Solution
|
||||
|
||||
*** Left :BMCOL:
|
||||
:PROPERTIES:
|
||||
:BEAMER_col: 0.5
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
valid([]).
|
||||
valid([Head|Tail]) :-
|
||||
fd_all_different(Head),
|
||||
valid(Tail).
|
||||
|
||||
sudoku(Puzzle, Solution) :-
|
||||
Solution = Puzzle,
|
||||
Puzzle = [S11, S12, S13, S14,
|
||||
S21, S22, S23, S24,
|
||||
S31, S32, S33, S34,
|
||||
S41, S42, S43, S44],
|
||||
|
||||
fd_domain(Solution, 1, 4),
|
||||
|
||||
Row1 = [S11, S12, S13, S14],
|
||||
Row2 = [S21, S22, S23, S24],
|
||||
Row3 = [S31, S32, S33, S34],
|
||||
Row4 = [S41, S42, S43, S44],
|
||||
#+end_src
|
||||
|
||||
*** Right :BMCOL:
|
||||
:PROPERTIES:
|
||||
:BEAMER_col: 0.5
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
Col1 = [S11, S21, S31, S41],
|
||||
Col2 = [S12, S22, S32, S42],
|
||||
Col3 = [S13, S23, S33, S43],
|
||||
Col4 = [S14, S24, S34, S44],
|
||||
|
||||
Square1 = [S11, S12, S21, S22],
|
||||
Square2 = [S13, S14, S23, S24],
|
||||
Square3 = [S31, S32, S41, S42],
|
||||
Square4 = [S33, S34, S43, S44],
|
||||
|
||||
valid([Row1, Row2, Row3, Row4,
|
||||
Col1, Col2, Col3, Col4,
|
||||
Square1, Square2, Square3, Square4]).
|
||||
#+end_src
|
||||
|
||||
** Eight Queens: The Problem
|
||||
- A board has eight queens.
|
||||
- Each queen has a row from 1-8 and a column from 1-8.
|
||||
- No two queens can share the same row.
|
||||
- No two queens can share the same column.
|
||||
- No two queens can share the same diagonal (southwest to northeast).
|
||||
- No two queens can share the same diagonal (northwest to southeast).
|
||||
|
||||
** Eight Queens: The Solution
|
||||
|
||||
*** Left :BMCOL:
|
||||
:PROPERTIES:
|
||||
:BEAMER_col: 0.5
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
valid_queen((Row, Col)) :-
|
||||
member(Col, [1,2,3,4,5,6,7,8]).
|
||||
valid_board([]).
|
||||
valid_board([Head|Tail]) :-
|
||||
valid_queen(Head), valid_board(Tail).
|
||||
|
||||
cols([], []).
|
||||
cols([(_, Col)|QueensTail], [Col|ColsTail]) :-
|
||||
cols(QueensTail, ColsTail).
|
||||
|
||||
diags1([], []).
|
||||
diags1([(Row, Col)|QueensTail],
|
||||
[Diagonal|DiagonalsTail]) :-
|
||||
Diagonal is Col - Row,
|
||||
diags1(QueensTail, DiagonalsTail).
|
||||
#+end_src
|
||||
|
||||
*** Right :BMCOL:
|
||||
:PROPERTIES:
|
||||
:BEAMER_col: 0.5
|
||||
:END:
|
||||
#+begin_src prolog
|
||||
diags2([], []).
|
||||
diags2([(Row, Col)|QueensTail],
|
||||
[Diagonal|DiagonalsTail]) :-
|
||||
Diagonal is Col + Row,
|
||||
diags2(QueensTail, DiagonalsTail).
|
||||
|
||||
eight_queens(Board) :-
|
||||
Board = [(1, _), (2, _), (3, _), (4, _),
|
||||
(5, _), (6, _), (7, _), (8, _)],
|
||||
valid_board(Board),
|
||||
|
||||
cols(Board, Cols),
|
||||
diags1(Board, Diags1),
|
||||
diags2(Board, Diags2),
|
||||
fd_all_different(Cols),
|
||||
fd_all_different(Diags1),
|
||||
fd_all_different(Diags2).
|
||||
#+end_src
|
||||
|
||||
** Exercises
|
||||
#+BEGIN_CENTER
|
||||
EXERCISES
|
||||
#+END_CENTER
|
||||
|
||||
* Wrapping Up
|
||||
|
||||
** Wrapping Up Prolog: Strengths
|
||||
- Natural-Language Processing
|
||||
- Games
|
||||
- Semantic Web
|
||||
- Artificial Intelligence
|
||||
- Scheduling
|
||||
|
||||
** Wrapping Up Prolog: Weaknesses
|
||||
- Utility
|
||||
- Very Large Data Sets
|
||||
- Mixing the Imperative and Declarative Models
|
||||
|
||||
** Final Thoughts
|
||||
#+BEGIN_QUOTE
|
||||
Prolog was a particularly poignant example of my evolving
|
||||
understanding. If you find a problem that's especially well suited for
|
||||
Prolog, take advantage. In such a setting, you can best use this
|
||||
rules-based language in combination with other general-purpose
|
||||
languages, just as you would use SQL within Ruby or Java.
|
||||
#+END_QUOTE
|
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