PROLOG – A VERSATILE LANGUAGE AND ITS APPLICATIONS

Prolog is a reasoning programming language. It plays an important role in human thinking. In comparison to other programming languages, Prolog is designed to a full programming language. Rationale is communicated as relations in Prolog. The logic being introduced is at the core of prolog. Running a query over the relation completes the computational plan. While ML is not the same as Deep Learning, the two words have become synonymous in recent years. Prolog is one of the most well-known Artificial Intelligence programming dialects, alongside LISP. Prolog was born out of a desire to develop a programming language that strongly relies on reasoning expressions rather than designing a programme by providing the machine a simple set of instructions. IBM Watson makes extensive use of Prolog. Prolog does not get much "publicity" or "buzz" these days, but it is still widely used. It has specific areas where it shines, as well as explicit approaches that guide well to its use. Inductive Logic Programming, Constraint Logic Programming, Solution Set Programming, and some NLP applications, makes extensive use of Prolog. Prolog is made to solve a number of Artificial Intelligence (AI) problems. There are a number of advantages in using Prolog as a programming language for developing AI applications. Here are a few examples:

Backtracking:

In any case, when an investigation route hits a dead end, Prolog's backtracking part retreats down the search path to find another path. This function makes Prolog especially well-suited to the numerous pursuit problems that AI experiences. It also has the added advantage of allowing you to find more than one solution to the problem if your backtracking options are limited until you've found the key solution. Since a large amount of AI problems can be resolved as a matter of finding the best path across the inquiry space, Prolog's underlying profundity, combined with backtracking, makes it suitable for such applications.

Pattern Matching and Unification:

The usage of integration to find the most general regular case of two equations or cases makes the design coordination of Prolog feasible. This ingenious function can assist AI in circumstances of critical reasoning where a vast number of decisions are made based on scenario coordination. This ability of Prolog can be incredibly used in a number of AI applications, including natural language processing, computer vision, and data mining etc.,

List Handling Mechanism:             

The nature of a list's details is important when dealing with AI problems (e.g. LISP which is additionally utilised for taking care of AI issues, represents " LISP Processing"). Records are built into Prolog, while they are not in most other dialects, making the development of Prolog programmes that involve list manipulation faster and easier. The recursive aspect of Rundown allows for extensive use of recursion in logical reasoning, which is an added bonus when dealing with AI problems with Prolog.

Prolog is well-suited to design applications that fix AI problems.  The field of Decision Support Systems is one such example. Aside from monetary decisions, therapeutic decisions may be supported by Prolog systems. A COMPUTER-based consultancy will also appear as a choice of emotionally supporting network. Natural Language Processing is another important area of AI in which Prolog contributes. Prolog is a simple and incredible asset for planning characteristic language because of its exemplary organising skill.

There are many knowledge-based Systems in the various AI applications that use Prolog. This is due to the fact that knowledge in certain systems is conveyed as laws. The Prolog sentence structure makes it easy to express these standards. Following that, a deduction should be feasible using the unification and query tool of Prolog. The quest and backtracking part of Prolog can manage any AI problem that can be solved with diagrams. As a result of this Graph Theory problems, can be solved. Scheduling and planning are another AI domain in which Prolog is used. The "Produce and Test" approach, allows the evaluation of competitor-created arrangements with less difficult task. The unification and pattern matching mechanism of Prolog can also be considered to be useful for AI problems in Computer Vision.

By

Mr. K Paul Nirmal Kumar, PGDM (AI & ML) Student &

Dr.Hemachandran K, Professor, Woxsen University, Hyderabad