Abstract
We consider homotopy type theory (HoTT) as a possible basis for Artificial General Intelligence (AGI) and study how it will frame the traditional problems of symbolic Artificial Intelligence (AI), which are not avoided, but can be addressed in a constructive way. We conclude that HoTT is suitable for building a language of a cognitive architecture, but it is not sufficient by itself to build an AGI system, which should contain grounded types and operation, including those that alter already defined types in a not strictly provable (within available types themselves) way.
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Acknowledgments
The authors are grateful to Ben Goertzel for useful references and ideas, which stimulated the study performed in the present paper. Thanks to Janet Adams and James Boyd for proofreading.
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Potapov, A., Bogdanov, V. (2022). Univalent Foundations of AGI are (not) All You Need. In: Goertzel, B., Iklé, M., Potapov, A. (eds) Artificial General Intelligence. AGI 2021. Lecture Notes in Computer Science(), vol 13154. Springer, Cham. https://doi.org/10.1007/978-3-030-93758-4_19
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DOI: https://doi.org/10.1007/978-3-030-93758-4_19
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