Analytical Inductive Programming as a Cognitive Rule Acquisition Devise
Ute Schmid, Martin O. Hofmann, Emanuel Kitzelmann · 2009
One of the most admirable characteristic of the human cognitive system is its ability to extract generalized rules covering regularities from example experience presented by or experienced from the environment.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 different domains, we believe that there exists a general mechanism to extract such rules from only positive examples 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 domains and can show that the Igor2 mechanism is able to learn the rules which can best describe systematic and productive behavior in such domains.