Texai is a knowledge-based software project to create artificial intelligence.

Revised July 6, 2009

Introduction

Texai is an knowledge-based, open source project to create artificial intelligence. The project’s approach is to first construct a bootstrap English dialog system whose goals are to acquire linguistic and common sense skills to improve its own performance. Next the system will acquire expertise in algorithms, and in Java programming for the purpose of explicitly representing its own behavior in the knowledge base (KB). Thus it will understand, revise, test and automatically compose its own source code. In parallel at this point, the system will acquire lexical and common sense knowledge from the glosses (word sense definitions) in the Texai lexicon, and begin to covert Wikipedia English text into KB statements, fleshing out the OpenCyc terms. In addition to scaling to many disparate users via Jabber chat from a single Texai instance, the system will be deployed as a virtual appliance to compute clusters and to a multitude of Internet users, where each instance hosts one or more nodes organized within an Albus Hierarchical Control System. These Albus Nodes (i.e. agents) will be organized into agencies, many mirroring current human organizations in which a node is a user’s proxy into the Albus hierarchy for some role. The artificial intelligence will then consist of a vast community of organizations whose members are Albus nodes, each quite intelligent with regard to its agency’s mission.

Initial Deployment Plan

The initial deployment of the English bootstrap dialog system was planned for June 23, 2009, which is Alan Turing’s birthday. But the release will be delayed for about six weeks until after I return from vacation to provide the agile level of support required for beta testing.

Texai will communicate, as an online chatbot, with volunteer mentors to acquire English noun plural word forms, and subsequently word sense meanings. Usage during the remainder of 2009 will confirm or deny the hypothesis that Texai will be able to figure out for itself a substantial portion of the WordNet word senses from their text definitions, after having learned the most frequently occurring definition word senses.

What is Available Now

The project’s knowledge base is stored in the Sesame RDF server. Because the initial knowledge base is large, it has been partitioned into separate Sesame repositories. These have been extracted into RDF and have been released in the file download section here. The project’s domain objects are persisted in Sesame using the RDF Entity Manager and semantic annotations. The RDF Entity Manager is released as a separate component. See the the file download section here.

News

Click on the Home link above for the latest blog posts.

  • I gave a tutorial on OpenCyc and commonsense reasoning at AGI-09, and the presentation is here. At the same conference I demonstrated a few utterances from the lexicon acquisition dialog, which is described in the poster presentation here.