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Prolog is a programming language used to solve logic-based problems. The problems are posed in the form of facts and rules and proven true or false by the help of a search algorithm known as backward chaining. It is an ideal language for defining logical queries, but not for numerically intensive processing. Programmers use prolog to define query languages used in expert systems. Prolog is also very good at doing inference on database relations, one reason being that prolog was built from the ground up specifically to handle such problems. Due its ability to do inference flexibly on relational data it has also been a major player in natural language processing (NLP) since the early 1980's, particularly thanks to John Foderaro's pioneering work at Yale University.
In earlier years, Prolog was used in teaching first year logic courses, when one needed to puzzle out what the notation actually meant and did. However nowadays other languages are preferred for this purpose. For instance, there is a new functional programming language which has been designed specifically to teach beginners propositional calculus, with an emphasis on truth-value assignments as values-in-functions rather than search trees and knowledge bases (this is called "Polymorphic First Degree" or PFD ).
The assignment operator in PFD ("=") will remain true even if all variables become provably false given some assignment of their respective possible values; this makes it easy to see that such an assignment does not exist. There is also a new multi-paradigm functional language called MALLET which will be discussed in a future post on this blog, when I demonstrate how to use it's built-in backtracking search engine for implementing searching algorithms, such as the CYK algorithm for finding all possible truth assignments for propositional boolean expressions (a.k.a., conjunctions of disjunctions of literals).
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Programming assignments in prolog are typically designed so that they require evaluating logical facts about some vocabulary with respect to other facts in order to produce desired conclusions, which is completely different from procedural languages such as C/C++, Java or Pascal where one writes procedures that are applied directly to data objects (as opposed to logic-based evaluation).
Projects done using Prolog consist of creating the formulae described above into logic-based problems using Prolog's grammar rules. Once these formulae are analyzed, we can solve the problems by searching for their solutions. The most common search algorithm used is Backward Chaining.
In prolog assignment, the first step in backward chaining is to consider all possible answers and output a list of these answers that includes the 'best' answer (usually considered as the shortest). If none of these results matches, then there is no solution. This portion of the program will often be called "the engine". The second step is to run through each potential solution (each sub-goal) and add it to a global database if it does not already exist. Each new fact created by backtracking enters into the background knowledge base (in short, BKB), which contains all facts that have been found by searching for a solution.
The third step is to use the remaining command and these new facts (which are collected in BKB) as input to a second search algorithm, which is called "the engine". This second step processes the new facts in order to solve any subgoals they support. The output of this step will provide more facts that could be used as additional data for the next iteration. This continues until no more solutions or goals can be generated from this process. If there are no further problems to be solved or if no more subgoals can be derived, then we have our answer.
Translation of a LR(0) grammar into Prolog is easy (simple BNF is sufficient), since the syntax of Prolog closely matches that of regular expressions and other types of formal grammars. The only difference between a simplified BNF grammar and an equivalent Prolog program is the declaration of data structures called predicates.
Look at this simple example:
An assign statement consists of two terms separated by an '=' symbol. Term refers to any string which does not start with a number. A number in a string is noted as '2.5E-4'. This means that the first term must be either an atom or another variable, while the second term can also be some other data structure such as a logical expression involving variables or constants and arithmetic operations on them (addition, multiplication, etc.).
You may view Prolog as a language of facts and rules.
An example of a college Prolog assignment:
X = 7.0 , Y = Pi , and Z = 12/X + 4/Y
The first two statements define values for X and Y respectively.
Next comes an assignment statement that defines value for Z using variables defined earlier and Arithmetic Operators (+, /).
Now we can treat the data in Z just as if it were assigned a value directly.
The third statement is not an assignment statement and so it does not define any new values.
It simply prints out the result obtained by evaluation of Z (using more arithmetic operators).
Hope this helps you to get started with your prolog assignment.
Here are some example code projects using prolog that you can use for coding if you don't want to ask for programming assignment help from the experts.
1. Create a Wiki from scratch in prolog
2. Natural language processing: Morphological analysis of english text. Identify noun phrases which contain multiple words (multiple stemmed words).
3. FizzBuzz: Write a program that prints out numbers from 1 - 100 but replaces multiples of 3 with fizz and 5 with buzz .
4. Word Guess: Create a program that guesses the most popular word given a set of hints.
5. Poker hands: Given a list of poker hands, rank them by how good they are. You can define some heuristics (e.g. flush beats straight).
6. Tetris: Write a program that plays tetris by generating random pieces and trying to form lines from them based on the current layout
7. Hangman: Play hangman with other people in chat rooms or instant messaging programs, saving each person's guesses so that you can check later if they guessed correctly or not. One strategy is to guess words already given as hints, but avoid words which have been used too much in previous games.
8. Mail Merge : Given a text file containing a set of records as fields (one per line) write code to merge it using fields as keys. For example if the fields are Name, Age and Address (in that order) then it should merge names like 'Chuck Norris' or 'John Smith' which have the same first name into one person with different last names.
9. Levenshtein distance: Given two words of variable length, compute how similar they are by computing the edit distance between them. This project is a bit more involved, but probably one of the best ways to get familiar with programming in prolog and natural language processing.
10. I Spy: Write a program which will accept any number of images and try to guess what they are. You can base your guesses on various attributes like color, shape or other features like lines or corners found in the image data or by using edge detection techniques like Hough transforms . Note that this is an advanced project which requires considerable research before making any significant progress on it.
11. Game AI: Design a game AI. Make sure it's not easily fooled into losing. Remember that the games will be played by humans so you'll want to make it easy for them to use your program (e.g. don't give complex instructions).
12. Create a dictionary of english words and their intended meaning / definition . This is a great way to build up your understanding of how word meanings are derived in natural language processing -- see etymology and word analysis as good places to start looking for inspiration on how this can be implemented.
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