Triple-CFN: Restructuring Conceptual Spaces for Enhancing Abstract Reasoning process

arXiv:2403.03190v1 Announce Type: new
Abstract: Abstract reasoning problems pose significant challenges to artificial intelligence algorithms, demanding cognitive capabilities beyond those required for perception tasks. This study introduces the Triple-CFN approach to tackle the Bongard-Logo problem, achieving notable reasoning accuracy by implicitly reorganizing the concept space of conflicting instances. Additionally, the Triple-CFN paradigm proves effective for the RPM problem with necessary modifications, yielding competitive results. To further enhance performance on the RPM issue, we develop the Meta Triple-CFN network, which explicitly …

abstract accuracy algorithms artificial artificial intelligence arxiv beyond capabilities challenges cognitive concept cs.cv instances intelligence logo perception process reasoning restructuring space spaces study tasks type