Turing Machine (C++ Implementation) is a Turing machine simulation that is defined by a series of input files. These include a metafile containing data related to some Turing machine, a states file containing a list of initial, halting, and internal states, an alphabet file of empty, input, and internal symbols, a transition file of transition rules, and input word files, which detail the input given on a tape.
HALoGEN is an extremely powerful and easy to use general-purpose natural language generation system. It consists of a symbolic generator, a forest ranker, and some sample inputs. The symbolic generator includes the Sensus Ontology dictionary based on WordNet. The forest ranker includes a 250 million word ngram language model (unigram, bigram, and trigram) trained on the Wall Street Journal newspaper text. The symbolic generator is written in LISP and requires a Lisp interpreter.
OMCSNetCPP is a C++ API and inference toolkit for accessing OMCSNet, a semantic network mined out of the Open Mind Common Sense knowledge base. The goal of this project is to provide a class library that allows programmers to easily add common sense reasoning capabilities to C++ applications.
The OMCSNet-WordNet project aims to improve the quality of the OMCSNet dataset by using automated processes to map WordNet synonym sets to OMCSNet concepts and import additional semantic linkage data from WordNet. It is based on OMCSNet 1.2, a semantic network and inference toolkit written in Python/Java. OMCSNet currently contains over 280,000 separate pieces of common sense information extracted from the raw OMCS dataset. This project is also based on WordNet, an online lexical reference system that in recent years has become a popular tool for AI researchers.
LinkGrammar-WN is a lexicon expansion for the Link Grammar Parser. The Link Grammar Parser is a syntactic parser of the English language that is capable of handling a wide variety of syntactic constructions and is considered quite robust. The LinkGrammar-WN project aims to import lexical information from WordNet in an effort to increase the size of the LGP lexicon. This project is of interest to anyone interested in NLP (natural language parsing) of English text.
The Orbital library is a Java class library providing object-oriented representations and algorithms for logic, mathematics, and computer science. It comprises theorem proving, computer algebra, search and planning, as well as machine learning algorithms. Generally speaking, the conceptual idea behind the Orbital library is to provide extensional services and components that surround the heart of many scientific applications, hence the name "Orbital library". In order to satisfy the requirements of high reusability, the design of this foundation class library favors flexibility, conceptual simplicity, and generalization. Many sophisticated problems can be solved easily with its adaptable components.