Symbolic Reasoning with Bounded Cognitive Resources
Paper in proceeding, 2014

We present a multi-domain computational model for symbolic reasoning that was designed with the aim of matching human performance. The computational model is able to reason by deduction, induction, and abduction. It begins with an arbitrary theory in a given domain and gradually extends this theory as new regularities are learned from positive and negative examples. At the core of the computational model is a cognitive model with bounded cognitive resources. The combinatorial explosion problem, which frequently arises in inductive learning, is tackled by searching for solutions inside this cognitive model only. By way of example, we show that the computational model can learn elements of two different domains, namely arithmetic and English grammar.


Claes Strannegård

Chalmers, Applied Information Technology (Chalmers)

University of Gothenburg

Abdul Rahim Nizamani

University of Gothenburg

Fredrik Engström

University of Gothenburg

Olle Häggström

Chalmers, Mathematical Sciences

University of Gothenburg

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

978-099119670-8 (ISBN)

36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Quebec, Canada,

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