<p>The growing complexity of next-generation distributed networks, and that of new environments more so known as 6G and beyond also implies that architectures must be computationally scalable as well as capable of self-reasoning and self-evolution. Nevertheless, the concept of cloud-top cooperation on the basis of deep learning and reinforcement learning employed in the conventional strategies may hardly forecast traffic, since the models are not transparent, too costly to run and insufficiently general. It has been presented in this manuscript, with Neuro-Symbolic Digital Twin Federation (NSDTF) principles, performant neural forecasting using symbolic reasoning, and physis-inspired optimization, as an evolutionary family of open-world networks evolved by Neuro-Symbolic that bring along self-evolving cloud-edge networks. Unlike in the past, when other digital twins are basically passive copies, the model enables federated twins to light up as dynamic knowledge synchronisation points collaborate across domains to optimize both the latency performance and energy efficient operation at the same time. These include neuro-symbolic edge inference to support context-aware decision making, federated synchronization of more than one digital twin to support resiliency, quantum-inspired cloud optimization to solve large-scale combinatorial resource allocation problems. It was also confirmed by simulated case study with a hybrid dataset, a combination of real-world IoT traffic traces and synthetic adversarial mobility conditions. Test Results: High average latency of up to 65% lowered, efficient power usage by 40%, rate of packet delivery exceeds 97% under dynamic circumstances. The astonishing peculiarity of the work is the fact that it views digital twins not only as objects of description and modifies them as learning agents that self-organize distributed networks to become resilient. This paper shows that sourcing subject matter expertise could be cost-efficient and develop customized models, but also opens the door to new research to explore evolution of distributed intelligent 7G autonomous infrastructures with neuro-symbolic and quantum-inspired mechanism in the core of the domain.</p>