  This study explores the concept of functional equivalence within the
framework of the Non-Axiomatic Reasoning System (NARS), specifically through
OpenNARS for Applications (ONA). Functional equivalence allows organisms to
categorize and respond to varied stimuli based on their utility rather than
perceptual similarity, thus enhancing cognitive efficiency and adaptability. In
this study, ONA was modified to allow the derivation of functional equivalence.
This paper provides practical examples of the capability of ONA to apply
learned knowledge across different functional situations, demonstrating its
utility in complex problem-solving and decision-making. An extended example is
included, where training of ONA aimed to learn basic human-like language
abilities, using a systematic procedure in relating spoken words, objects and
written words. The research carried out as part of this study extends the
understanding of functional equivalence in AGI systems, and argues for its
necessity for level of flexibility in learning and adapting necessary for
human-level AGI.
