A good overview is given by: Pei Wang's AGI Intro
Novamente's general cognition/reasoning system. Includes NLP subsystem, reasoning, 3d virtual avatar, robotics interfaces. Open-source, GPL license.
NARS, the Non-Axiomatic Reasoning System, is a general-purpose reasoning system. Several white-papers. Inspired OpenCog. (OpenCog claims to overcome certain limitations in NARS) OpenNARS is Pei Wang's implementation. Released under GPLv2.
Performs textual entailment using a first-order-logic (FOL) theorem prover, and an FOL model builder. Written in prolog(!) Non-free license, bars commercial use.
Aims to couple common-sense knowledge-basees systems to natural langauge text processing. Open source project.
An intelligent agent, communicating by email. Built for the US Navy. Based on Baar's Global Workspace Theory. Answers only one question "What do I do next?". See Tutorial
The MultiNet paradigm - Knowledge Representation with Multilayered Extended Semantic Networks by Hermann Helbig. Wires up NLP processing to hard-wired upper ontology, and adds reasoning. No source code available.
Seems primarily aimed at robots.
no code available.
Commercialized "Heierarchical Temporal Memory"
SNePS is a knowledge representation, reasoning, and acting (KRRA) system. See also the Wikipedia page See also a paper by Shapiro, part of the SNePS group.
Developed by Hakia Labs, proprietary, commercial software for taking NLP input and generating ontological frames/expressions from it. See also ontologicalsemantics.com.
Big ones include
Common-sense knowledgebase. Large. GPL license. Users can edit data online, at http://torg.media.mit.edu:3000/
Collection of english-language sentences, rather than using a strict upper ontology. This is actually quite conventient, if you have a good NLP input system, as it helps avoid the strictures of pre-designed ontologies; and rather gets you to deal with the structure of your NLP-to-KR layter. From MIT. -- large -- 700K sentences
Yago is a huge semantic knowledge base, consisting primarily of information about entities. Contains 2M entities, and 20M facts about them. The YAGO-NAGA project also includes SOFIE, a system for automatically extending an ontology via NLP and reasoning.
Semantic network.
See also: Wordnet::Similarity A perl module implementing various word similarity measures from Wordnet data. i.e. Thesaurus-like.
Licensing is unclear.
SUMO WP article. Includes an open source Sigma knowledge engineering environment, includes a theorem prover. Sigma uses KIF.
"The largest formal public ontology in existence", availble under GPL. (although OpenCyc is arguably bigger, and is free.) Has mappings to WordNet.
Large KB under artistic license. Source for engine not available. KB seems messy and capricious. The uppper ontology is not clear.
Common sense KB, available in CycL. GPL'ed
A knowledge representation system. Conceptual Graph Interchange Format is an ISO standard. See also "Common Logic Interchange Format (CLIF)", which is more lisp-like.
Seems well-engineered. Actual KB is slim. Source not available. Might be a dead project??
Provides a firm theoretical foundation for representing ontologies; no actual data. OWL version of GFO under a modified BSD license. Examples include the periodic table of elements, amino acids. See also WP article.
See also datalog for a decent list of databases/reasoners that implement the dtalog query system.
See also Open Source Rule Engines in Java
Uses probabalistic analog of first-order logic, kind-of. Ideal for uncertain inference. Beta available now. In the process of being ported to Opencog. GNU GPLv3 Affero license.
Prolog engine, open source. Supports tabling/memoing, well-founded negation. This is one of the fastest inference engines out there, per results of the Madrid 2009 Semantic Web OpenRuleBench results. Personally, I suspect that this is because of a strong grounding in inference and language design theory on the part of the developers.
Prolog engine. for performance, adds "demand-driven indexing". This is one of the fastest inference engines out there, per results of the Madrid 2009 Semantic Web OpenRuleBench results. Personally, I suspect that this is because of a strong grounding in inference and language design theory on the part of the developers.
Inference engine, bottom-up. Implements the datalog query system. Has "Magic Set" optimization. Implemented in Java. Immature? LGPL license.
PowerLoom uses a fully expressive, logic-based representation language (a variant of KIF). It uses a natural deduction inference engine that combines forward and backward chaining to derive what logically follows from the facts and rules asserted in the knowledge base. Has interfaces to common-lisp, C++ and Java. GPL license.
Inference engine, specifically tailored to work well with Python. Features:
No website. spotty download. See announce for details. Appears to be one-time-only code snapshot release.
Primarily an inference engine coupled to an ontology. GPL license.
Drools is a business rule management system (BRMS) and an enhanced Rules Engine implementation, ReteOO, based on Charles Forgy's Rete algorithm tailored for the Java language. Despite using RETE, this is possibly the slowest inference engines out there, as well as the least stable (per WWW Madric 2009 Semantic Web OpenRuleBench results).
Function symbols. Meant for event processing, not data processing ...
Use Boolean SAT for traditional propositional logic solvers, use SMT for solvers that include arithmetic expressions.
A wiki containing an extensive listing of software oand other things is at ACLWeb, and in particular, at the Tools and Software page. A small list is at the NLP Resources wiki page at agiri.org.
A particularly important theory is Dick Hudson's Word Grammar.
Other NLP resources include:
See also http://www.singinst.org/research/researchareas
Includes a shallow parser, a sentence splitter, entity detection, sense annotation (using wordnet senses), etc.
The IMS Open Corpus Workbench (CWB) is a collection of tools for managing and querying large text corpora (100 M words and more) with linguistic annotations. Its central component is the flexible and efficient query processor CQP.