# 6G Cognitive Information Theory: A Mailbox Perspective
## 5 Proactive Interaction Network Based on Digital Twin  
Furthermore, a new theory is needed to realize tight coupling between the communication system and AI and the change from data transmission to value transmission. The future 6G should not only realize faster transmission, lower transmission latency, and better reliability, with terahertz-order (THz) communication, integrated sky-earth communication, visible light communication (VLC) and AI, but also the transmission of data value and support for the interaction of values. Thus, it is necessary for 6G communication systems to realize the integration of algorithms into data and computing platform (i.e., computing power), that is, algorithms should be embedded into the generation, acquisition, transmission, integration, and visualization of data, to realize the transmission of data values. This theory is described as the mailbox theory, that is, with the introduction of a mailbox, the deep integration of algorithms, data, and computing powers in 6G communication systems is realized.  
Today, AI chips are more powerful than previously, and intelligent applications based on deep learning are used more extensively. In addition, a larger number of devices are accessing the network. The future network will introduce the seamless connection between the network, the physical world, and humans, realizing the seamless connection between the physical space, information space, and human world. Thus, future networks need to integrate AI algorithms into the cloud-edge network; namely, they need to deploy an AI algorithm not only at the cloud, but also at the edge cloud and terminal to realize better real-time interaction between the physical and information spaces.  
As discussed above, if the function of proactive interaction is to be realized in 6G networks, real-time interaction between physical space and information space is required. In fact, it is difficult for devices in physical space to interact with information space in realtime. In order to make the network have the function of proactive interaction, based on digital twin technology, the digital twin network (DTN) is designed with four key elements (network twin data, model, mapping, and interaction), to realize efficient interaction between physical space and information space. 6G networks include three layers: (i) The first layer is the physical communication layer, including the entity unit of the network, that is, the network entity with communication, caching, computing, and intelligence mentioned in intelligent networks. (ii) The second layer is a digital twin layer. Firstly, a network entity unit operates data and historical data to form the data source of a digital twin layer, then a model is established based on data source, and in combination with application requirements, and interaction of the model are realized. (iii) The third layer is the information layer, namely the information transmission in 6G network.  
However, most of the existing AI algorithms have been deployed on the cloud, and these algorithms have been designed by humans, which means that well-marked dataset and training layers shall be established, but they have poor robustness and generalization ability. Moreover, their training processes are conducted in a centralized way, and such a cloud-based way can hardly meet the requirements of applications showing strong interaction in the physical world. Therefore, deploying algorithms at the edge cloud and terminals will not only provide better interaction with the physical world, but also better adapt to the changes in the environment and to users relying on multi-agent learning.