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.
@article{arxiv.2502.01834,
title = {Building a Cognitive Twin Using a Distributed Cognitive System and an Evolution Strategy},
author = {Wandemberg Gibaut and Ricardo Gudwin},
journal= {arXiv preprint arXiv:2502.01834},
year = {2025}
}
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first submitted on 09/22/2022, published on 01/20/2025