![]() The use of this library was necessary due to the decision of use Prolog in order to implement the Planner Algorithm. All those actions have been implemented using another Python library, namely PySWIP, a Python - SWI-Prolog bridge enabling to query SWI-Prolog in Python programs. Instead in case of a command it has to run the planner algorithm in order to reach the required goal. ![]() In case of an assertion, the program has to add facts from it to the knowledge base, according to the Planner Algorithm, while in case of a query it has to answer it according to the knowledge base. Therefore it can act differently according to the cases. Once obtained the tagged tree structure of the entered sentence, the program explores it in order to understand what the user wants. Once the user has entered the sentence, the program takes, tokenizes and transforms it in a part-of- speech tagged tree structure. This library allows to build Python programs which work with human language data, providing text processing for classification, tokenization, tagging and parsing. Indeed the program uses a Python library for NLP, namely Natural Language Toolkit (NLTK). In order to recognize the type of sentence the program uses the Natural Language Processing (NLP), a branch of AI that helps computers understand, interpret and manipulate human language. Once entered a sentence, the program recognize what kind it is and react accordingly to the result. Using the program the user has only to type sentences (reasonables in the domain of interest) that can be assertions, queries or commands. The goal of this project was to implement a program that allows users to solve the blocks world problem interacting only using the natural language.
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