# Multiple-Valued Logic Modelling for Agents Controlled via Optical Networks
## 1 Introduction  
### Data Protection Problem of Network Robotics  
Modern fiber optics networks have become the base for high throughput communication networks combining 5/6G Internet [1, 2], big data services [3], quantum key distribution (QKD) lines [4, 5], and futuristic quantum computing systems [6]. However, now they are also a good candidate for the massive distant control of autonomous robotic devices, which involves the Internet of unmanned transport vehicles (IoV) [7], industrial systems [8], medicine nursing robots [9], the Internet of Things (IoT) [10], and smart cities [11], supported by mechatronics drives reproducing human movements [12] and computer vision systems [13, 14]. Such autonomous robots are planned to be used as separate devices [15] in a collective of collaborating agents commonly called the multiagent system (MAS) [16] or in a global network-centric system [17]. All such designs are based on methods of artificial intelligence (AI), which is the method of imitating the individual and collective work of people [15]. As mobile robotic agents need wireless data links, communication networks should combine fiber optics lines and wired Ethernet pairs with wireless Wi-Fi, Bluetooth, and atmospheric satellite or terrestrial laser lines [4, 5, 18] (see Figure 1). Modern smartphones [19] supporting AI algorithms can also be used for the distant control of robots. Thus, modern networks add many new participants of network data exchange and enlarge the number of possible hardware and software platforms for the interaction of robotic agents with distant users. The modelling of such systems becomes very complicated as, besides network communications, it should describe human decision making and collective work procedures [15]. The limiting factor for network robotics is the data protection problem, as modern networks and especially their wireless components cannot provide the necessary level of protection from attacks and data leakages [20, 21]. Quantum key distribution systems [4, 5, 18, 22, 23] partially improve the situation, but even they donot exclude specific quantum attacks and malicious impacts on supporting classical components. Unfortunately, data leakages due to disloyal personnel have become more of an actual problem than computer viruses and attacks aimed at stationary network nodes [23]. Furthermore, distant mobile robotic agents have many additional vulnerabilities, as current computer vision and decision-making systems [14; 15] cannot replace human monitoring. At the same time, mass and unexpensive network robotics need to avoid trusted network nodes, exploiting the special design of servers and intense human control [24; 25] that are mainly appropriate for large corporate systems. In order to enhance the security level for the distant control of autonomous agents and MASs, it is necessary to combine quantum and traditional data protection methods with new AI algorithms, which now are grounded in concepts of agent and MASs [7; 8; 9; 10; 11; 26; 27; 28]. The presented paper is devoted to the original properties of multiple-valued logic (MVL) [29], which provides the possibility to design new schemes of agents based on multiparametrical logic functions and easily provides the modelling of various procedures in a high-dimensional space of parameters [30]. MVL functions can also realize schemes of secret data coding for one-time cipher pads and random keys [31], to accumulate random data into the scheme of random oracle [32], to model the theoretically proven and most protected position-based cryptography protocol by [PERSON] [33], and to realize data classification procedures [30]. That is why the actual task of secured distant work of robotic agents and MASs [34] is the potential field of applications for MVL functions [29; 30], which now needs the integration of disparate algorithms and schemes into the whole data-protection agent, combining quantum and classical data coding methods.