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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.14011 |
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| _version_ | 1866909694905286656 |
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| author | Totaro, Paolo Mangiante, Alberto |
| author_facet | Totaro, Paolo Mangiante, Alberto |
| contents | This article proposes a method to formalise models of cognitive processes grounded in experience, considering experience from the perspective of a living system and not from that of an observer of the living system. The perspective of a living system is defined by the need of the system to preserve the vital equilibria. The method is based on an algorithmic schema that we call Environment Generative Operator (EGO) and uses a self-referential language developed for this purpose which we call E-language. EGO simulates cognitive processes as operations on neuron assemblies as understood by Hebb. In this article we present an EGO prototype (EGO-P) which has already been implemented and tested. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_14011 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Conceptual and Design Principles for a Self-Referential Algorithm Mimicking Neuronal Assembly Functions Totaro, Paolo Mangiante, Alberto Neural and Evolutionary Computing Robotics This article proposes a method to formalise models of cognitive processes grounded in experience, considering experience from the perspective of a living system and not from that of an observer of the living system. The perspective of a living system is defined by the need of the system to preserve the vital equilibria. The method is based on an algorithmic schema that we call Environment Generative Operator (EGO) and uses a self-referential language developed for this purpose which we call E-language. EGO simulates cognitive processes as operations on neuron assemblies as understood by Hebb. In this article we present an EGO prototype (EGO-P) which has already been implemented and tested. |
| title | Conceptual and Design Principles for a Self-Referential Algorithm Mimicking Neuronal Assembly Functions |
| topic | Neural and Evolutionary Computing Robotics |
| url | https://arxiv.org/abs/2507.14011 |