Distributed Artificial Intelligence is attracting interest day by day. In this paper, the authors introduce an innovative methodology for distributed learning of Particle Swarm Optimization-based Fuzzy Cognitive Maps in a privacy-preserving way. The authors design a training scheme for collaborative FCM learning that offers data privacy compliant with the current regulation. This method is applied to a cancer detection problem, proving that the performance of the model is improved by the Federated Learning process, and obtaining similar results to the ones that can be found in the literature.

翻译：分布式人工智能日益受到关注。本文提出了一种创新的方法论，用于以隐私保护方式对基于粒子群优化的模糊认知图进行分布式学习。作者设计了一种协作式FCM训练方案，在满足现行法规的数据隐私要求下运行。该方法应用于癌症检测问题，证明联邦学习过程提升了模型性能，并取得了与文献报道相媲美的结果。