Transparent Neural Networks: Integrating Concept Formation and Reasoning
Paper in proceeding, 2012

We present the transparent neural networks, a graph-based computational model that was designed with the aim of facilitating human understanding. We also give an algorithm for developing such networks automatically by interacting with the environment. This is done by adding and removing structures for spatial and temporal memory. Thus we automatically obtain a monolithic computational model which integrates concept formation with deductive, inductive, and abductive reasoning.

transparent neural networks

inductive reasoning

developmental robotics

deductive reasoning

concept formation

Author

Claes Strannegård

University of Gothenburg

Chalmers, Applied Information Technology (Chalmers), Cognition and Communication

Olle Häggström

University of Gothenburg

Chalmers, Mathematical Sciences, Mathematical Statistics

Johan Wessberg

University of Gothenburg

Christian Balkenius

Lund University

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 7716 302-311

Subject Categories

Philosophy

Philosophy, Ethics and Religion

Computer Science

DOI

10.1007/978-3-642-35506-6_31

More information

Latest update

8/17/2021