Programming in Prolog is very different from programming in a procedural language. In Prolog you supply a database of facts and rules; you can then perform queries on the database. The basic unit of Prolog is the predicate, which is defined to be true. A predicate consists of a head and a number of arguments. For example: cat(tom). This enters into the database the fact that 'tom' is a 'cat'. More formally, 'cat' is the head, and 'tom' is the single argument. Here are some sample queries you could ask a Prolog interpreter basing on this fact: is tom a cat? ?- cat(tom). yes. ...

See also:

Prolog, Prolog - Data types, Prolog - Atoms, Prolog - Numbers, Prolog - Variables, Prolog - Terms, Prolog - Lists, Prolog - Strings, Prolog - Facts, Prolog - Rules, Prolog - Evaluation, Prolog - Negation, Prolog - Execution, Prolog - Parsing, Prolog - Parser example, Prolog - Examples, Prolog - QuickSort, Prolog - Towers of Hanoi, Prolog - Computer Algebra, Prolog - Implementations, Prolog - Extensions, Prolog - Resources, Prolog - Conferences, Prolog - References, Prolog - Tutorial introductions, Prolog - Tools, Prolog - External resources, Prolog - Books/ Tutorials

Read more here: » Prolog: Encyclopedia II - Prolog - Facts

See also:

Prolog, Prolog - Data types, Prolog - Atoms, Prolog - Numbers, Prolog - Variables, Prolog - Terms, Prolog - Lists, Prolog - Strings, Prolog - Facts, Prolog - Rules, Prolog - Evaluation, Prolog - Negation, Prolog - Execution, Prolog - Parsing, Prolog - Parser example, Prolog - Examples, Prolog - QuickSort, Prolog - Towers of Hanoi, Prolog - Computer Algebra, Prolog - Implementations, Prolog - Extensions, Prolog - Resources, Prolog - Conferences, Prolog - References, Prolog - Tutorial introductions, Prolog - Tools, Prolog - External resources, Prolog - Books/ Tutorials

Read more here: » Prolog: Encyclopedia II - Prolog - Examples

Prolog is a logical language, so in theory the programmer shouldn't care about how it executes. However, sometimes it is prudent to take into account how the inference algorithm works, to prevent a Prolog program from running for an unnecessarily long time. For example, we can write code to count the number of elements in a list. elems([],0). elems([H|T], X) :- elems(T, Y), X is Y + 1. This simply says: If the list is empty, the number of elements is zero. If the list is non-empty, then X is one higher than Y, which is the number of elements in the remainder of ...

See also:

Prolog, Prolog - Data types, Prolog - Atoms, Prolog - Numbers, Prolog - Variables, Prolog - Terms, Prolog - Lists, Prolog - Strings, Prolog - Facts, Prolog - Rules, Prolog - Evaluation, Prolog - Negation, Prolog - Execution, Prolog - Parsing, Prolog - Parser example, Prolog - Examples, Prolog - QuickSort, Prolog - Towers of Hanoi, Prolog - Computer Algebra, Prolog - Implementations, Prolog - Extensions, Prolog - Resources, Prolog - Conferences, Prolog - References, Prolog - Tutorial introductions, Prolog - Tools, Prolog - External resources, Prolog - Books/ Tutorials

Read more here: » Prolog: Encyclopedia II - Prolog - Execution

Prolog was an early programming language that was billed by its designers as being based on mathematical logic. The basis for the claim that Prolog was that it used backward chaining from goal to subgoal (as in Planner). Schematically, the process is: goal :- subgoal1, ..., subgoaln. which states that in order to prove goal, it is sufficient to prove subgoal1See also:

Logic programming, Logic programming - Basis in mathematical logic, Logic programming - Prolog, Logic programming - Limitations of Prolog as logic programming, Logic programming - Inductive logic, Logic programming - Application domains, Logic programming - History

Read more here: » Logic programming: Encyclopedia II - Logic programming - Prolog

Prolog does not employ data types in the way common programming languages usually do. We may rather speak about Prolog lexical elements instead of data types. Prolog - Atoms. The text constants are introduced by means of atoms. An atom is a sequence consisting of letters, numbers and underscores, which begins with a lower-case letter. Usually, if a non-alphanumeric atom is needed, it is surrounded with apostrophes (e.g. 'an atom containing spaces')............ Prolog - Numbers. Most Prolog implementations do not distinguish integers from real numbers. ...

See also:

Prolog, Prolog - Data types, Prolog - Atoms, Prolog - Numbers, Prolog - Variables, Prolog - Terms, Prolog - Lists, Prolog - Strings, Prolog - Facts, Prolog - Rules, Prolog - Evaluation, Prolog - Negation, Prolog - Execution, Prolog - Parsing, Prolog - Parser example, Prolog - Examples, Prolog - QuickSort, Prolog - Towers of Hanoi, Prolog - Computer Algebra, Prolog - Implementations, Prolog - Extensions, Prolog - Resources, Prolog - Conferences, Prolog - References, Prolog - Tutorial introductions, Prolog - Tools, Prolog - External resources, Prolog - Books/ Tutorials

Read more here: » Prolog: Encyclopedia II - Prolog - Data types

In mathematical logic, in particular as applied to computer science, a unification of two terms is a join (in the lattice sense) with respect to a specialisation order. That is, we suppose a preorder on a set of terms, for which t* ≤ t means that t* is obtained from t by substituting some term(s) for one or more free variables in t. The unification u of s and t, if it exists, is a term that is a substitution instance of both s and t. Any common substitution instance of s ...

Including:

• Unification - Unification in Prolog
• Unification - Examples of unification

Read more here: » Unification: Encyclopedia - Unification

Inference is the act or process of drawing a conclusion based solely on what one already knows. Suppose you see rain on your window - you can infer from that, quite trivially, that the sky is grey. Looking out the window would have yielded the same fact, but through a process of perception, not inference (note however that perception itself can be viewed as an inferential process). Inference is studied within several different fields. Human inference (i.e. how humans draw conclusions) is traditionally studied within the field o ...

Including:

• Inference - The accuracy of inductive and deductive inferences
• Inference - Valid inferences
• Inference - An example: the classic syllogism
• Inference - Automatic logical inference
• Inference - An example: inference using Prolog
• Inference - Inference and uncertainty
• Inference - Common sense and uncertain reasoning
• Inference - Bayesian statistics and probability logic
• Inference - Frequentist statistical inference
• Inference - Fuzzy logic

Read more here: » Inference: Encyclopedia - Inference

Backward chaining is one of the two main methods of reasoning when using inference rules. The other is forward chaining. Backward chaining starts with a list of goals (or a hypothesis) and works backwards to see if there are data available that will support any of these goals. An inference engine using backward chaining would search the inference rules until it finds one which has a Then clause that matches a desired goal. If the If clause of that inference rule is not known to be true, then it is added to the list of goals (in order for your goal to be confirmed ...

Read more here: » Backward chaining: Encyclopedia - Backward chaining

Clipper is a computer programming language that is used to create software programs that originally operated primarily under DOS. Although it is a powerful general-purpose programming language, it was primarily used to create database/business programs. Clipper was originally created in 1985 as a compiler for dBASE III, a very popular database language at the time. Compiling dBASE code changes it from interpreted code (i.e., human-readable source code), which must be interpreted every time each line of code is executed, ...

Read more here: » Clipper programming language: Encyclopedia - Clipper programming language

The cut-elimination theorem is the central result establishing the significance of the sequent calculus. It was originally proved by Gerhard Gentzen in his landmark paper "Investigations in Logical Deduction" for the systems LJ and LK formalising intuitionistic and classical logic respectively. The cut-elimination theorem states that any judgement that possesses a proof in the sequent calculus that makes use of the cut rule also possesses a cut-free proof ...

Read more here: » Cut-elimination theorem: Encyclopedia - Cut-elimination theorem

The concept of unification is one of the main ideas behind Prolog. It represents the mechanism of binding the contents of variables and can be viewed as a kind of one-time assignment. In Prolog, this operation is denoted by symbol "=". In traditional Prolog, a variable X which is uninstantiated—i.e. no previous unifications were performed on it—can be unified with an atom, a term, or another uninstantiated variable, thus effectively becoming its alias. In many modern Prolog dialects and in first-order logic cal ...

See also:

Unification, Unification - Unification in Prolog, Unification - Examples of unification

Read more here: » Unification: Encyclopedia II - Unification - Unification in Prolog

Contrarily to Prolog, the semantics of answer set programs do not depend on a specific order of evaluation of the rules and of the atoms within each rule. The complexity of checking the existence of an answer set for a program and the complexity of checking whether a program entails a literal range from P to the second level of the polynomial hierarchy depending on a set of conditions (e.g., stratification, disjunction in the head) a program may or may not satisfy.

See also:

Answer set programming, Answer set programming - Syntax, Answer set programming - Semantics, Answer set programming - Comparison Complexity and Implementations

Read more here: » Answer set programming: Encyclopedia II - Answer set programming - Comparison Complexity and Implementations

Logic Programming is an idea that has been investigated in the context of artificial intelligence since at least the time of John McCarthy [1958] which proposed "programs to manipulate in a suitable formal language (most likely a part of the predicate calculus) common instrumental statements. The basic program will draw immediate conclusions from a list of premises. These conclusions will be either declarative or imperative sentences. When an imperative sentence is deduced the pr ...

See also:

Logic programming, Logic programming - Basis in mathematical logic, Logic programming - Prolog, Logic programming - Limitations of Prolog as logic programming, Logic programming - Inductive logic, Logic programming - Application domains, Logic programming - History

Read more here: » Logic programming: Encyclopedia II - Logic programming - History

The semantic of a program is based on its answer sets, each answer set being a set of literals. For programs not containing negation-as-failure, the semantic of a program is based on the concepts of closure and minimality: A program is closed under a set of literals if the set contains at least a literal in the head of a rule whenever it contains all literals in its body. A set of literals is an answer set of a program if it is minimal (under set containme ...

See also:

Answer set programming, Answer set programming - Syntax, Answer set programming - Semantics, Answer set programming - Comparison Complexity and Implementations

Read more here: » Answer set programming: Encyclopedia II - Answer set programming - Semantics

In concrete terms for Actor systems, typically we cannot observe the details by which the arrival order of messages for an Actor is determined. Attempting to do so affects the results and can even push the indeterminacy elsewhere. e.g., see metastability in electronics and arbiters. Instead of observing the internals of arbitration processes of Actor computations, we await outcomes. Indeterminacy in arbiters produces indeterminacy in Actors. The reason tha ...

See also:

Indeterminacy in computation, Indeterminacy in computation - A limitation of logic programming, Indeterminacy in computation - Arrival order indeterminacy, Indeterminacy in computation - A limitation of logic due to lack of information, Indeterminacy in computation - Prolog-like concurrent systems were claimed to be based on mathematical logic, Indeterminacy in computation - Logical operations and system efficiency, Indeterminacy in computation - Indeterminacy in other models of computation

Read more here: » Indeterminacy in computation: Encyclopedia II - Indeterminacy in computation - Arrival order indeterminacy

However, Prolog did not include the negation or disjunction of mathematical logic because both individually and together they cause a lot of trouble for the Prolog interpreter. For example if negation were included, the following Prolog program not Q. Q :- P. would be unable to prove not P even though it follows by the rules of mathematical logic. This is an illustration of the fact that Prolog is unable to prove many of ...

See also:

Logic programming, Logic programming - Basis in mathematical logic, Logic programming - Prolog, Logic programming - Limitations of Prolog as logic programming, Logic programming - Inductive logic, Logic programming - Application domains, Logic programming - History

Read more here: » Logic programming: Encyclopedia II - Logic programming - Limitations of Prolog as logic programming

Keith Clark, Herve Gallaire, Steve Gregory, Vijay Saraswat, Udi Shapiro, Kazunori Ueda, etc. developed a family of Prolog-like concurrent message passing systems using unification of shared variables and data structure streams for messages. Claims were made that these systems were based on mathematical logic. This kind systems was used as the basis of the Japanese Fifth Generation Project (ICOT). Like the Actor model, the Prolog-like concurrent systems were based on message passing and consequently were subject to the same indetermina ...

See also:

Indeterminacy in computation, Indeterminacy in computation - A limitation of logic programming, Indeterminacy in computation - Arrival order indeterminacy, Indeterminacy in computation - A limitation of logic due to lack of information, Indeterminacy in computation - Prolog-like concurrent systems were claimed to be based on mathematical logic, Indeterminacy in computation - Logical operations and system efficiency, Indeterminacy in computation - Indeterminacy in other models of computation

Read more here: » Indeterminacy in computation: Encyclopedia II - Indeterminacy in computation - Prolog-like concurrent systems were claimed to be based on mathematical logic

For any IT application, the business rules change more frequently than the rest of the application code. Rules Engines or Inference Engines are the pluggable software components that separate the business rules from the application code. This allows the business users to modify the rules frequently without the need of IT intervention and hence allowing the applications to be more adaptable with the dynamic rules. In previous generation applications, data was meant to be dynamic which was supposed to be operated upon by the logic and rules to get the desired results. Data Dynamics are no longer the only need of the hour but the focus ...

See also:

Rule engine, Rule engine - IT use, Rule engine - Is it worth the investment?, Rule engine - Design strategies, Rule engine - Types of rule engines

Read more here: » Rule engine: Encyclopedia II - Rule engine - IT use

In Prolog, one aspect of the Barber paradox can be expressed by a self-referencing clause: shaves(barber,X) :- male(X), not shaves(X,X). male(barber). where negation as failure is assumed. If we apply the stratification test known from Datalog, the predicate shaves is exposed as unstratifiable since it is defined recursively over its negation. ...

See also:

Barber paradox, Barber paradox - The paradox, Barber paradox - History, Barber paradox - In prolog, Barber paradox - In literature

Read more here: » Barber paradox: Encyclopedia II - Barber paradox - In prolog

Quicksort's inner loop, which performs the partition, is amenable to optimization on typical modern machines for two main reasons: All comparisons are being done with a single pivot value, which can be stored in a register. The list is being traversed sequentially, which produces very good locality of reference and cache behavior for arrays. This close fit with modern architectures makes quicksort one of the fastest sorting algorithms on average. Because of this excellent average performance and simple implementation, quicksort has become one of the ...

See also:

Quicksort, Quicksort - The algorithm, Quicksort - Version with in-place partition, Quicksort - Performance details, Quicksort - Choosing a better pivot, Quicksort - Partitioning concerns, Quicksort - Other optimizations, Quicksort - Competitive sorting algorithms, Quicksort - Formal analysis, Quicksort - Randomized quicksort expected complexity, Quicksort - Average complexity, Quicksort - Space complexity, Quicksort - Relationship to selection, Quicksort - Sample implementations, Quicksort - C, Quicksort - C++, Quicksort - Haskell, Quicksort - J, Quicksort - Joy, Quicksort - Prolog, Quicksort - SML, Quicksort - Footnotes

Read more here: » Quicksort: Encyclopedia II - Quicksort - Performance details