NARS (Non-Axiomatic Reasoning System) is a general-purpose reasoning system, coming from my study of Artificial Intelligence (AI) and Cognitive Sciences (CogSci).
What makes NARS different from conventional reasoning systems is its ability to learn from its experience and to work with insufficient knowledge and resources.
NARS attempts to uniformly explain and reproduce many cognitive facilities, including reasoning, learning, planning, reacting, perceiving, categorizing, prioritizing, remembering, decision making, and so on.
The research results include a theory of intelligence, a formal model of the theory, and a computer implementation of the model.
The ultimate goal of this research is to fully understand the mind, as well as to build thinking machines.
What is new:
- NARS Introduction - a brief overview
- NAL Specification - the logic of NARS, formally defined and up-to-date
- Formalization of Evidence - revised version
- AGI-09 - two papers and a demo
- A General Theory of Intelligence - draft version 0.1 finished
- Artificial General Intelligence : A Gentle Introduction - revised
- Suggested Education for Future AGI Researchers - revised
- Demo applet of Open-NARS 1.1.2, with examples of multi-step inference process