Artificial General Segmentation

DOI

10.2991/agi.2010.31How to use a DOI?

Abstract

We argue that the ability to find meaningful chunks in sequential input is a core cognitive ability for artificial general intelligence, and that the Voting Experts algorithm, which searches for an information theoretic signature of chunks, provides a general implementation of this ability. In support of this claim, we demonstrate that VE successfully finds chunks in a wide variety of domains, solving such diverse tasks as word segmentation and morphology in multiple languages, visually recognizing letters in text, finding episodes in sequences of robot actions, and finding boundaries in the instruction of an AI student. We also discuss further desirable attributes of a general chunking algorithm, and show that VE possesses them.

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  - Daniel Hewlett
AU  - Paul Cohen
PY  - 2010/06
DA  - 2010/06
TI  - Artificial General Segmentation
BT  - Proceedings of the 3d Conference on Artificial General Intelligence (2010)
PB  - Atlantis Press
SP  - 142
EP  - 147
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2010.31
DO  - 10.2991/agi.2010.31
ID  - Hewlett2010/06
ER  -