Building a Cognitive Twin Using a Distributed Cognitive System and an Evolution Strategy
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917912201134080 |
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| author | Gibaut, Wandemberg Gudwin, Ricardo |
| author_facet | Gibaut, Wandemberg Gudwin, Ricardo |
| contents | This work presents a technique to build interaction-based Cognitive Twins (a computational version of an external agent) using input-output training and an Evolution Strategy on top of a framework for distributed Cognitive Architectures. Here, we show that it's possible to orchestrate many simple physical and virtual devices to achieve good approximations of a person's interaction behavior by training the system in an end-to-end fashion and present performance metrics. The generated Cognitive Twin may later be used to automate tasks, generate more realistic human-like artificial agents or further investigate its behaviors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_01834 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Building a Cognitive Twin Using a Distributed Cognitive System and an Evolution Strategy Gibaut, Wandemberg Gudwin, Ricardo Artificial Intelligence Neural and Evolutionary Computing This work presents a technique to build interaction-based Cognitive Twins (a computational version of an external agent) using input-output training and an Evolution Strategy on top of a framework for distributed Cognitive Architectures. Here, we show that it's possible to orchestrate many simple physical and virtual devices to achieve good approximations of a person's interaction behavior by training the system in an end-to-end fashion and present performance metrics. The generated Cognitive Twin may later be used to automate tasks, generate more realistic human-like artificial agents or further investigate its behaviors. |
| title | Building a Cognitive Twin Using a Distributed Cognitive System and an Evolution Strategy |
| topic | Artificial Intelligence Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2502.01834 |