The Logic of Hebbian Learning
We present the logic of Hebbian learning, a dynamic logicwhose semantics1 are expressed in terms of a layered neuralnetwork learning via Hebb’s associative learning rule. Its lan-guage consists of modality Tφ (read “typically φ,” formalizedas forward propagation), conditionals φ ⇒ ψ (read “typi-call...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2022-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
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| Online Access: | https://journals.flvc.org/FLAIRS/article/view/130735 |
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| author | Caleb Kisby Saúl Blanco Lawrence Moss |
| author_facet | Caleb Kisby Saúl Blanco Lawrence Moss |
| author_sort | Caleb Kisby |
| collection | DOAJ |
| description | We present the logic of Hebbian learning, a dynamic logicwhose semantics1 are expressed in terms of a layered neuralnetwork learning via Hebb’s associative learning rule. Its lan-guage consists of modality Tφ (read “typically φ,” formalizedas forward propagation), conditionals φ ⇒ ψ (read “typi-cally φ are ψ”), as well as dynamic modalities [φ+]ψ (read“evaluate ψ after performing Hebbian update on φ”). We giveaxioms and inference rules that are sound with respect to theneural semantics; these axioms characterize Hebbian learningand its interaction with propagation. The upshot is that thislogic describes a neuro-symbolic agent that both learns fromexperience and also reasons about what it has learned. |
| format | Article |
| id | doaj-art-20d63dcb4e364d0fb7b35c324b480cbe |
| institution | OA Journals |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-20d63dcb4e364d0fb7b35c324b480cbe2025-08-20T01:52:18ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622022-05-013510.32473/flairs.v35i.13073566934The Logic of Hebbian LearningCaleb Kisby0Saúl Blanco1Lawrence Moss2Department of Computer Science, Indiana University BloomingtonDepartment of Computer Science, Indiana University BloomingtonDepartment of Mathematics, Indiana University BloomingtonWe present the logic of Hebbian learning, a dynamic logicwhose semantics1 are expressed in terms of a layered neuralnetwork learning via Hebb’s associative learning rule. Its lan-guage consists of modality Tφ (read “typically φ,” formalizedas forward propagation), conditionals φ ⇒ ψ (read “typi-cally φ are ψ”), as well as dynamic modalities [φ+]ψ (read“evaluate ψ after performing Hebbian update on φ”). We giveaxioms and inference rules that are sound with respect to theneural semantics; these axioms characterize Hebbian learningand its interaction with propagation. The upshot is that thislogic describes a neuro-symbolic agent that both learns fromexperience and also reasons about what it has learned.https://journals.flvc.org/FLAIRS/article/view/130735neurosymbolic aihebbian learningdynamic logicsknowledge representation and reasoningnonmonotonic reasoningpreference upgrade |
| spellingShingle | Caleb Kisby Saúl Blanco Lawrence Moss The Logic of Hebbian Learning Proceedings of the International Florida Artificial Intelligence Research Society Conference neurosymbolic ai hebbian learning dynamic logics knowledge representation and reasoning nonmonotonic reasoning preference upgrade |
| title | The Logic of Hebbian Learning |
| title_full | The Logic of Hebbian Learning |
| title_fullStr | The Logic of Hebbian Learning |
| title_full_unstemmed | The Logic of Hebbian Learning |
| title_short | The Logic of Hebbian Learning |
| title_sort | logic of hebbian learning |
| topic | neurosymbolic ai hebbian learning dynamic logics knowledge representation and reasoning nonmonotonic reasoning preference upgrade |
| url | https://journals.flvc.org/FLAIRS/article/view/130735 |
| work_keys_str_mv | AT calebkisby thelogicofhebbianlearning AT saulblanco thelogicofhebbianlearning AT lawrencemoss thelogicofhebbianlearning AT calebkisby logicofhebbianlearning AT saulblanco logicofhebbianlearning AT lawrencemoss logicofhebbianlearning |