Principles of Programming Languages
UNIT - VIII
Logic Programming Languages
Topics
* Introduction
* A Brief Introduction to Predicate Calculus
* Predicate Calculus and Proving Theorems
* An Overview of Logic Programming
* The Origins of Prolog
* The Basic Elements of Prolog
* Deficiencies of Prolog
* Applications of Logic Programming
Introduction
* Logic programming languages, sometimes called declarative programming languages
* Express programs in a form of symbolic logic
* Use a logical inferencing process to produce results
* Declarative rather that procedural:
> Only specification of results are stated (not detailed procedures for producing them)
Proposition
* A logical statement that may or may not be true
> Consists of objects and relationships of objects to each other
Symbolic Logic
* Logic which can be used for the basic needs of formal logic:
> Express propositions
> Express relationships between propositions
> Describe how new propositions can be inferred from other propositions
* Particular form of symbolic logic used for logic programming called predicate calculus
Object Representation
* Objects in propositions are represented by simple terms: either constants or variables
* Constant: a symbol that represents an object
* Variable: a symbol that can represent different objects at different times
> Different from variables in imperative languages
Compound Terms
* Atomic propositions consist of compound terms
* Compound term: one element of a mathematical relation, written like a mathematical function
> Mathematical function is a mapping
> Can be written as a table
Parts of a Compound Term
* Compound term composed of two parts
> Functor: function symbol that names the relationship
> Ordered list of parameters (tuple)
* Examples:
student(jon)
like(seth, OSX)
like(nick, windows)
like(jim, linux)
Forms of a Proposition
* Propositions can be stated in two forms:
> Fact: proposition is assumed to be true
> Query: truth of proposition is to be determined
* Compound proposition:
> Have two or more atomic propositions
> Propositions are connected by operators
lClausal Form
* Too many ways to state the same thing
* Use a standard form for propositions
* Clausal form:
> B1 B2 … Bn A1 A2 … Am
> Means if all the As are true, then at least one B is true
* Antecedent: right side
* Consequent: left side
Predicate Calculus and Proving Theorems
* A use of propositions is to discover new theorems that can be inferred from known axioms and theorems
* Resolution: an inference principle that allows inferred propositions to be computed from given propositions
Resolution
* Unification: finding values for variables in propositions that allows matching process to succeed
* Instantiation: assigning temporary values to variables to allow unification to succeed
* After instantiating a variable with a value, if matching fails, may need to backtrack and instantiate with a different value
Theorem Proving
* Basis for logic programming
* When propositions used for resolution, only restricted form can be used
* Horn clause - can have only two forms
> Headed: single atomic proposition on left side
> Headless: empty left side (used to state facts)
* Most propositions can be stated as Horn clauses
Overview of Logic Programming
* Declarative semantics
> There is a simple way to determine the meaning of each statement
> Simpler than the semantics of imperative languages
* Programming is nonprocedural
> Programs do not state now a result is to be computed, but rather the form of the result
The Origins of Prolog
* University of Aix-Marseille
> Natural language processing
* University of Edinburgh
> Automated theorem proving
Terms
* Edinburgh Syntax
* Term: a constant, variable, or structure
* Constant: an atom or an integer
* Atom: symbolic value of Prolog
* Atom consists of either:
> a string of letters, digits, and underscores beginning with a lowercase letter
> a string of printable ASCII characters delimited by apostrophes
Terms: Variables and Structures
* Variable: any string of letters, digits, and underscores beginning with an uppercase letter
* Instantiation: binding of a variable to a value
> Lasts only as long as it takes to satisfy one complete goal
* Structure: represents atomic proposition
functor(parameter list)
Fact Statements
* Used for the hypotheses
* Headless Horn clauses
female(shelley).
male(bill).
father(bill, jake).
Rule Statements
* Used for the hypotheses
* Headed Horn clause
* Right side: antecedent (if part)
> May be single term or conjunction
* Left side: consequent (then part)
> Must be single term
* Conjunction: multiple terms separated by logical AND operations (implied)
Example Rules
ancestor(mary,shelley):- mother(mary,shelley).
* Can use variables (universal objects) to generalize meaning:
parent(X,Y):- mother(X,Y).
parent(X,Y):- father(X,Y).
grandparent(X,Z):- parent(X,Y), parent(Y,Z).
sibling(X,Y):- mother(M,X), mother(M,Y),
father(F,X), father(F,Y).
Goal Statements
* For theorem proving, theorem is in form of proposition that we want system to prove or disprove
> goal statement
* Same format as headless Horn
man(fred)
* Conjunctive propositions and propositions with variables also legal goals
father(X,mike)
Inferencing Process of Prolog
* Queries are called goals
* If a goal is a compound proposition, each of the facts is a subgoal
* To prove a goal is true, must find a chain of inference rules and/or facts. For goal Q:
B :- A
C :- B
…
Q :- P
* Process of proving a subgoal called matching, satisfying, or resolution
Approaches
* Bottom-up resolution, forward chaining
> Begin with facts and rules of database and attempt to find sequence that leads to goal
> Works well with a large set of possibly correct answers
* Top-down resolution, backward chaining
> Begin with goal and attempt to find sequence that leads to set of facts in database
> Works well with a small set of possibly correct answers
* Prolog implementations use backward chaining
Subgoal Strategies
* When goal has more than one subgoal, can use either
> Depth-first search: find a complete proof for the first subgoal before working on others
> Breadth-first search: work on all subgoals in parallel
* Prolog uses depth-first search
> Can be done with fewer computer resources
Backtracking
* With a goal with multiple subgoals, if fail to show truth of one of subgoals, reconsider previous subgoal to find an alternative solution: backtracking
* Begin search where previous search left off
* Can take lots of time and space because may find all possible proofs to every subgoal
Simple Arithmetic
* Prolog supports integer variables and integer arithmetic
* Is operator: takes an arithmetic expression as right operand and variable as left operand
A is B / 17 + C
* Not the same as an assignment statement!
Example
speed(ford,100).
speed(chevy,105).
speed(dodge,95).
speed(volvo,80).
time(ford,20).
time(chevy,21).
time(dodge,24).
time(volvo,24).
distance(X,Y) :- speed(X,Speed),
time(X,Time),
Y is Speed * Time.
Trace
* Built-in structure that displays instantiations at each step
* Tracing model of execution - four events:
> Call (beginning of attempt to satisfy goal)
> Exit (when a goal has been satisfied)
> Redo (when backtrack occurs)
> Fail (when goal fails)
Example
likes(jake,chocolate).
likes(jake,apricots).
likes(darcie,licorice).
likes(darcie,apricots).
trace.
likes(jake,X),
likes(darcie,X).
List Structures
* Other basic data structure (besides atomic propositions we have already seen): list
* List is a sequence of any number of elements
* Elements can be atoms, atomic propositions, or other terms (including other lists)
[apple, prune, grape, kumquat]
[] (empty list)
[X | Y] (head X and tail Y)
Append Example
append([], List, List).
append([Head | List_1], List_2, [Head | List_3]) :-
append (List_1, List_2, List_3).
Reverse Example
reverse([], []).
reverse([Head | Tail], List) :-
reverse (Tail, Result),
append (Result, [Head], List).
Deficiencies of Prolog
* Resolution order control
* The closed-world assumption
* The negation problem
* Intrinsic limitations
Applications of Logic Programming
* Relational database management systems
* Expert systems
* Natural language processing
Summary
* Symbolic logic provides basis for logic programming
* Logic programs should be nonprocedural
* Prolog statements are facts, rules, or goals
* Resolution is the primary activity of a Prolog interpreter
* Although there are a number of drawbacks with the current state of logic programming it has been used in a number of areas
SUBJECTIVE
1) Write a LISP function that calculates sum of numbers using a vector.
2) What is functional programming? Explain its merits and demerits.
3) Give brief description about data objects in LISP.
4) Give the LISP function reverse(L) which reverses a given list L
5) Explain various operations that can be performed on atoms and lists in LISP. Give examples
6) Write a LISP program segment that generates factorial of n
7) Explain some of the important functions of LISP
8) Explain about LISP interpreter.
9) Describe briefly about expressions, functions and exceptions in meta language.
10) Explain about functions in ML
11) Describe briefly about expressions in ML
12) Explain structures and arrays in ML. Give examples.
13) Explain main features of imperative languages.
14) Write a LISP function fib(n) that computes nth Fibonacci number.