AndreFCruz

%% P 7.3
% Versao estendida do problema de colorir um mapa.
% Para alem do problema original, apresenta restricoes de exclusao,
%  condicoes positivas/negativas, diferencas e preferencias flexiveis.

:- use_module(library(lists)).
:- use_module(library(clpfd)).

%% Base de Factos
paises(5).

AndreFCruz

% Pergunta 3.3

:- use_module(library(lists)).
:- use_module(library(clpfd)).

objecto(piano, 3, 30).
objecto(cadeira, 1, 10).
objecto(cama, 3, 15).
objecto(mesa, 2, 15).
homens(4).

AndreFCruz

%% P9

:- use_module(library(lists)).
:- use_module(library(clpfd)).

% numPecas(Id, Min, Max)
numPecas(1, 5, 15).
numPecas(2, 2, 6).
numPecas(3, 5, 10).
numPecas(4, 7, 12).

AndreFCruz

%% P 7.2

:- use_module(library(lists)).
:- use_module(library(clpfd)).

% docente(Nome, Sexo, Start, End) -> pode dar aulas que comecem de Start a End
docente(pedro, m, 3, 6).
docente(joana, f, 3, 4).
docente(ana, f, 2, 5).
docente(joao, m, 2, 4).

AndreFCruz

:- use_module(library(lists)).
:- use_module(library(clpfd)).

%% P13 - Prova modelo algures no grupo do fb
% attend(+, -, -)
attend(FilmList, Goings, Worth) :-
  length(FilmList, N),
  length(Goings, N),
  domain(Goings, 0, 1),

AndreFCruz

:- use_module(library(lists)).
:- use_module(library(clpfd)).

% P 4.a)
table6(L) :-
  %% Indices in list L
  % Asdrubal=1, Bernardete=2, Cristalinda=3
  % Demetrio=4, Eleuterio=5, Felismina=6
  L = [Asdr, Bern, Crist, Demet, Eleut, Felism],
  domain(L, 1, 6),

AndreFCruz

%% Exame PLOG 15-16
%% P13

:- use_module(library(lists)).
:- use_module(library(clpfd)).

% concelho(Nome, Distancia, NEleitoresIndecisos)
concelho(x, 120, 410).
concelho(y, 10, 800).
concelho(z, 543, 2387).

AndreFCruz

% Solving Magic Squares using Sicstus PROLOG

:- use_module(library(clpfd)).
:- use_module(library(lists)).

matrixDomain([], _).
matrixDomain([Row | Matrix], N) :-
  NSquared is N * N,
  length(Row, N),
  domain(Row, 1, NSquared),

AndreFCruz

# Solving Magic Squares using Google's ortools
# https://github.com/google/or-tools

from ortools.constraint_solver import pywrapcp
import sys

def main(n=4):
    # Create the solver.
    solver = pywrapcp.Solver('Magic square')
    # declare variables

AndreFCruz

%% Code from http://www.emse.fr/~picard/cours/ai/minimax/#sec-3

% minimax(Pos, BestNextPos, Val)
% Pos is a position, Val is its minimax value.
% Best move from Pos leads to position BestNextPos.
minimax(Pos, BestNextPos, Val) :-                     % Pos has successors
    bagof(NextPos, move(Pos, NextPos), NextPosList),
    best(NextPosList, BestNextPos, Val), !.

minimax(Pos, _, Val) :-                     % Pos has no successors