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Table of Content
- Idea
- Step by step instructions to Solve Problems with Logic Programming
- Realities
- Rules
- Useful Packages in python programming
- Checking for Prime Numbers
- Solving Puzzles
Introduction
In this section, we will center rational programming and how it helps
in Artificial Intelligence.
We definitely realize that rationale is the investigation of standards
of right-thinking or in straightforward words, it is the investigation of what
comes after what. For instance, in the event that two articulations are valid,
at that point we can induce any third explanation from it.
Idea
Rationale Programming is the blend of two words, rationale, and
programming. Rationale Programming is a programming worldview in which the
issues are communicated as realities and rules by program proclamations however
inside an arrangement of formal rationale. Much the same as other programming
ideal models like item situated, useful, revelatory, and procedural, and so
on., it is likewise a specific method to move toward programming.
Step by step instructions to Solve Problems with Logic Programming
Rationale Programming utilizes realities and rules for taking care of
the issue. That is the reason they are known as the structure squares of Logic
Programming. An objective should be determined for each program in rationale
programming. To see how an issue can be fathomed in rationale programming, we
have to think about the structure squares − Facts and Rules −
Realities
As a matter of fact, each rationale program needs realities to work with
so it can accomplish the given objective. Realities fundamentally are genuine
explanations about the program and information. For instance, Delhi is the
capital of India.
Rules
All things considered, rules are the limitations which permit us to make
decisions about the difficult area. Rules fundamentally composed as sensible
provisos to communicate different realities. For instance, on the off chance
that we are assembling any game, at that point all the guidelines must be
characterized.
Rules are essential to take care of any issue in Logic Programming.
Rules are essentially obvious end result which can communicate the realities.
Keeping is the punctuation of rule −
A∶− B1,B2,...,Bn.
Here, An is the head and B1, B2, ... Bn is the body.
For instance − ancestor(X,Y) :- father(X,Y).
ancestor(X,Z) :- father(X,Y), ancestor(Y,Z).
This can be perused as, for each X and Y, if X is the dad of Y and Y is
a precursor of Z, X is the predecessor of Z. For each X and Y, X is the
precursor of Z, if X is the dad of Y and Y is a predecessor of Z.
Introducing Useful Packages in python programming
For beginning rationale programming in Python, we have to introduce the
accompanying two bundles −
Kanren
It gives us an approach to streamlining the manner in which we made code
for business rationale. It lets us express the rationale as far as rules and
realities. The accompanying order will assist you with introducing kanren
SymPy
SymPy is a Python library for representative arithmetic. It means to
turn into a full-included PC polynomial math framework (CAS) while keeping the
code as straightforward as conceivable so as to be fathomable and effectively
extensible. The accompanying order will assist you with introducing SymPy −
Instances of Logic Programming
Followings are a few models which can be tackled by rationale
programming −
Coordinating numerical articulations
In reality, we can locate obscure qualities by utilizing rationale
programming in an extremely compelling manner. The accompanying Python code
will assist you with coordinating a numerical articulation –
Consider bringing in the accompanying bundles first –
from kanren import run, var,
fact
from kanren.assoccomm import eq_assoccomm as eq
from kanren.assoccomm import commutative, associative
from kanren.assoccomm import eq_assoccomm as eq
from kanren.assoccomm import commutative, associative
We have to characterize the numerical tasks which
we are going to utilize −
add = 'add'
mul = 'mul'
Both expansion and duplication are informative procedures. Consequently,
we have to determine it and this should be possible as follows –
fact(commutative, mul)
fact(commutative, add)
fact(associative, mul)
fact(associative, add)It is obligatory to characterize factors; this should be possible as
follows –
a, b = var('a'), var('b')
We have to coordinate the articulation with the first example. We have
the accompanying unique example, which is essentially (5+a)*b −
Original_pattern = (mul, (add, 5, a), b)
We have the accompanying two articulations to coordinate with the first
example –
exp1 = (mul, 2, (add, 3, 1))
exp2 = (add,5,(mul,8,1))
Yield can be printed
with the accompanying order –
Subsequent to running
this code, we will get the accompanying yield −
The main yield speaks
to the qualities for an and b. The principal articulation coordinated the first
example and restored the qualities for an and b yet the subsequent articulation
didn't coordinate the first example thus nothing has been returned.
Checking for Prime Numbers
With the assistance of rationale programming, we can locate the prime
numbers from a rundown of numbers and can likewise produce prime numbers. The
Python code given beneath will locate the prime number from a rundown of
numbers and will likewise produce the initial 10 prime numbers. Let us
initially consider bringing in the accompanying bundles –
from kanren import isvar, run, membero
from kanren.core import success, fail, goaleval, condeseq, eq, var
from sympy.ntheory.generate import prime, isprime
import itertools as itPresently, we will characterize a capacity called prime_check which will
check the prime numbers dependent on the given numbers as information.
def prime_check(x):
if isvar(x):
return condeseq([(eq,x,p)] for p in map(prime, it.count(1)))
else:
return success if isprime(x) else failPresently, we have to announce a variable which will be utilized –
x = var()
print((set(run(0,x,(membero,x,(12,14,15,19,20,21,22,23,29,30,41,44,52,62,65,85)),
(prime_check,x)))))
print((run(10,x,prime_check(x))))The output of the above code will be as follows –
Solving Puzzles
Rationale programming can be utilized to take care of
numerous issues like 8-puzzles, Zebra puzzle, Sudoku, N-sovereign, and so on.
Here we are taking a case of a variation of Zebra puzzle which is as per the
following –
There are five houses.
The English man lives in the red house.
The Swede has a dog.
The Dane drinks tea.
The green house is immediately to the left of the white house.
They drink coffee in the green house.
The man who smokes Pall Mall has birds.
In the yellow house they smoke Dunhill.
In the middle house they drink milk.
The Norwegian lives in the first house.
The man who smokes Blend lives in the house next to the house with cats.
In a house next to the house where they have a horse, they smoke Dunhill.
The man who smokes Blue Master drinks beer.
The German smokes Prince.
The Norwegian lives next to the blue house.
They drink water in a house next to the house where they smoke Blend.We are fathoming it
for the inquiry who claims zebra with the assistance of Python.
Let us import the
fundamental bundles –
from kanren import *
from kanren.core import lall
import timePresently, we have to characterize two capacities − left() and next() to
check whose house is gone out –
def left(q, p, list):
return membero((q,p), zip(list, list[1:]))
def next(q, p, list):
return conde([left(q, p, list)], [left(p, q, list)])Now, we will declare a variable house as follows –
houses = var()
We have to
characterize the standards with the assistance of lall bundle as follows.
There are 5 houses –
rules_zebraproblem = lall(
(eq, (var(), var(), var(), var(), var()), houses),
(membero,('Englishman', var(), var(), var(), 'red'), houses),
(membero,('Swede', var(), var(), 'dog', var()), houses),
(membero,('Dane', var(), 'tea', var(), var()), houses),
(left,(var(), var(), var(), var(), 'green'),
(var(), var(), var(), var(), 'white'), houses),
(membero,(var(), var(), 'coffee', var(), 'green'), houses),
(membero,(var(), 'Pall Mall', var(), 'birds', var()), houses),
(membero,(var(), 'Dunhill', var(), var(), 'yellow'), houses),
(eq,(var(), var(), (var(), var(), 'milk', var(), var()), var(), var()), houses),
(eq,(('Norwegian', var(), var(), var(), var()), var(), var(), var(), var()), houses),
(next,(var(), 'Blend', var(), var(), var()),
(var(), var(), var(), 'cats', var()), houses),
(next,(var(), 'Dunhill', var(), var(), var()),
(var(), var(), var(), 'horse', var()), houses),
(membero,(var(), 'Blue Master', 'beer', var(), var()), houses),
(membero,('German', 'Prince', var(), var(), var()), houses),
(next,('Norwegian', var(), var(), var(), var()),
(var(), var(), var(), var(), 'blue'), houses),
(next,(var(), 'Blend', var(), var(), var()),
(var(), var(), 'water', var(), var()), houses),
(membero,(var(), var(), var(), 'zebra', var()), houses))Now, run the solver with the preceding constraints −
solutions = run(0, houses, rules_zebraproblem)
With the assistance of
the accompanying code, we can separate the yield from the solver –
The accompanying code
will help print the arrangement –
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