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m Disambiguating links to Tokenization (link changed to Tokenization (lexical analysis)) using DisamAssist. |
Jario.Zhang (talk | contribs) Add some new result comparing Symbolic AI and Connectionist AI. |
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{{cite web |last1=Rossi |first1=Francesca |title=Thinking Fast and Slow in AI |url=https://aaai-2022.virtualchair.net/plenary_13.html |publisher=AAAI |access-date=5 July 2022}}</ref><ref name="Selman">
{{cite web |last1=Selman |first1=Bart |title=AAAI Presidential Address: The State of AI |url=https://aaai-2022.virtualchair.net/plenary_2.html |publisher=AAAI |access-date=5 July 2022}}</ref> and addressing areas that both approaches have difficulty with, such as [[Commonsense reasoning|common-sense reasoning]].{{sfn|Marcus |Davis|2019}}
It is worth noting that, from a theoretical perspective, Zhang et al. have demonstrated that mainstream knowledge representation formalisms are, in fact, recursively isomorphic, provided they possess equivalent expressive power<ref>{{Cite journal |last=Zhang |first=Heng |last2=Jiang |first2=Guifei |last3=Quan |first3=Donghui |date=2025-04-11 |title=A Theory of Formalisms for Representing Knowledge |url=https://ojs.aaai.org/index.php/AAAI/article/view/33674 |journal=Proceedings of the AAAI Conference on Artificial Intelligence |language=en |volume=39 |issue=14 |pages=15257–15264 |doi=10.1609/aaai.v39i14.33674 |issn=2374-3468}}</ref>. This finding implies that there is no fundamental distinction between using symbolic or connectionist knowledge representation formalisms for the realization of [[artificial general intelligence]] (AGI). Moreover, the existence of recursive isomorphisms suggests that different technical approaches can, in practice, draw insights from one another.
== History ==
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