User:Rhmccullough/Sandbox/History

History
Looking at previous generations of Artificial Intelligence languages, there are two features that are clearly missing: easy readability; a solid epistemological foundation for definitions and context.

The readability problem is clearly evident in the Semantic Web environment, and is typified by the contrast between XML and N3 (aka Notation 3). When writing formal documents, XML is the usual choice. But when people are working together informally, and striving for ease of understanding, N3 is a frequent choice.

The epistemology problem is not as clearly evident, but it has been a thorn in the side of Artificial Intelligence researchers for decades. Terry Winograd, one of the successful early researchers in Natural Language processing, said : Language is a process of communication between people, and is   inextricably enmeshed in the knowledge that those people have about the world. That knowledge is not a neat collection of    definitions and axioms, complete, concise and consistent. Rather it is a collection of concepts designed to manipulate ideas. It is in fact incomplete, highly redundant, and often inconsistent. There is no self-contained set of "primitives" from which everything else can be defined. Definitions are circular, with the meaning of each concept depending on the other concepts.

Conceptual Graphs appeared to provide a good foundation for definitions. However, visual graphs are just too simple; a written language is needed to express the complexities of the real world. A foundation for context was even more elusive; researchers could not agree on a definition of context:

..the fields of knowledge representation and natural language.. In both fields, one observes a huge spectrum of answers to an   important question in the technical agenda: "What is context?" This broad range of answers reflects both the confusion about context and the enormous difficulties in handling it.

The mKR language combines a restricted natural language, Simple English, with a strong epistemology to provide readability, definitions and context.

In 2002, the developers of mKR and RDF compared the two languages in a W3C email forum. This forum produced a better understanding of both languages, but did not lead to any significant changes in either language. The developers later compared the mKR and OWL languages; this time a significant change was made in the OWL language. Property Restrictions were added to emulate the genus-differentia definitions of the mKR language.

At the suggestion of the RDF/OWL developers, a practical mKR language interface was developed for the Stanford University TAP knowledge base and the OpenCyc knowledge base. A simple mKR language interface was also developed for Amazon.com and Google. mKE (my Knowledge Explorer) was enhanced to read RDF files.

The most recent changes in mKE (my Knowledge Explorer) provide command-line options to initialize the knowledge base with concepts from a language chosen by the user. Language options include RDF, OWL, OpenCyc, TAP, Amazon, Google.