Relational Local Iterative Compression

DOI

10.2991/agi.2010.11How to use a DOI?

Abstract

Compression in the program space is of high importance in Artificial General Intelligence. Since maximal data compression in the general sense is not possible to achieve, it is necessary to use approximate algorithms, like AIXIt;l. This paper introduces a system that is able to compress data locally and iteratively, in a relational description language. The system thus belongs to the anytime algorithm family: the more time spent, the better it performs. The locality property is also well-suited for AGI agents to allow them to focus on "interesting" parts of the data.

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/).

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TY  - CONF
AU  - Laurent Orseau
PY  - 2010/06
DA  - 2010/06
TI  - Relational Local Iterative Compression
BT  - Proceedings of the 3d Conference on Artificial General Intelligence (2010)
PB  - Atlantis Press
SP  - 53
EP  - 54
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2010.11
DO  - 10.2991/agi.2010.11
ID  - Orseau2010/06
ER  -