Analytical Inductive Programming as a Cognitive Rule Acquisition Devise

DOI

10.2991/agi.2009.35How to use a DOI?

Abstract

One of the most admirable characteristic of the hu- man cognitive system is its ability to extract gener- alized rules covering regularities from example expe- rience presented by or experienced from the environ- ment. Humans' problem solving, reasoning and verbal behavior often shows a high degree of systematicity and productivity which can best be characterized by a competence level reflected by a set of recursive rules. While we assume that such rules are different for dif- ferent domains, we believe that there exists a general mechanism to extract such rules from only positive ex- amples from the environment. Our system Igor2 is an analytical approach to inductive programming which induces recursive rules by generalizing over regularities in a small set of positive input/output examples. We applied Igor2 to typical examples from cognitive do- mains and can show that the Igor2 mechanism is able to learn the rules which can best describe systematic and productive behavior in such domains.

Copyright

© 2009, 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  - Ute Schmid
AU  - Martin Hofmann
AU  - Emanuel Kitzelmann
PY  - 2009/06
DA  - 2009/06
TI  - Analytical Inductive Programming as a Cognitive Rule Acquisition Devise
BT  - Proceedings of the 2nd Conference on Artificial General Intelligence (2009)
PB  - Atlantis Press
SP  - 164
EP  - 169
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2009.35
DO  - 10.2991/agi.2009.35
ID  - Schmid2009/06
ER  -