Analytical Inductive Programming as a Cognitive Rule Acquisition Devise
Ute Schmid, Martin Hofmann, Emanuel Kitzelmann
Available Online June 2009.
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- 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.
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Cite this article
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 Artificiel General Intelligence (2009) PB - Atlantis Press SP - 164 EP - 169 SN - 1951-6851 UR - https://doi.org/10.2991/agi.2009.35 DO - https://doi.org/10.2991/agi.2009.35 ID - Schmid2009/06 ER -