Stochastic Grammar Based Incremental Machine Learning Using Scheme

DOI

10.2991/agi.2010.27How to use a DOI?

Abstract

Gigamachine is our initial implementation of an Artificial General Intelligence (AGI system) in the O'Caml language with the goal of building Solomonoff's Phase 1 machine that he proposed as the basis of a quite powerful incremental machine learning system (Sol02). While a lot of work remains to implement the full system, the present algorithms and implementation demonstrate the issues in building a realistic system. Thus, we report on our ongoing research to share our experience in designing such a system. In this extended abstract, we give an overview of our present implementation, summarize our contributions, discuss the results obtained, the limitations of our system, our plans to overcome those limitations, potential applications, and future work. The reader is referred to (Sch04; Sol02; Sol09) for a background on general-purpose incremental machine learning. The precise technical details of our ongoing work may be found in (Ozk09), which focuses on our algorithmic contributions. The discussion here is not as technical but assumes basic knowledge of universal problem solvers.

Copyright

© 2010, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Eray Ozkural
AU  - Cevdet Aykanat
PY  - 2010/06
DA  - 2010/06
TI  - Stochastic Grammar Based Incremental Machine Learning Using Scheme
BT  - Proceedings of the 3d Conference on Artificial General Intelligence (2010)
PB  - Atlantis Press
SP  - 126
EP  - 127
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2010.27
DO  - 10.2991/agi.2010.27
ID  - Ozkural2010/06
ER  -