## 3 Results: AGA Logic Variables for Scene Description and Dialog Communications
### Communication Module and the Dialog Protocol
## 7 Discussion

Although the properties of agents discussed in this paper can be realized by means of AGA easily enough, the used method certainly has some restrictions. The first of them follows just from the main advantage of AGA to describe large-scale systems, given by the large number of logic variables and corresponding rows in the truth table. The \"manual\" design of the multi-parametric AGA truth table is the time wasteful procedure, but the more difficult problem here is the wasteful logic minimization of the AGA function by the consensus method [70], which was considered in detail in [75], in 2016. Such minimization for the AGA function is the tool to shorten the computing time, and if one periodically updates the acquired data set containing many zero values, the real computing time can vary significantly and disturb the clocking scheme. Such a specific feature is to be taken into account, as either one should combine minimization procedures with the other to support fixed time bands for used subroutines. Another known problem of AGA minimization [75] is that it leads to the multi-criteria optimization task for the choice of so-called \"don't care states\" during the minimization procedure. In fact, here one should define additional values of AGA function (i.e., to choose additional rows with non-zero logic constants in the truth table). It is not a problem for a purely mathematician task, but the selection of \"don't care state\" [70] for physical parameters may be a tricky choice. That is why one should design special monitoring procedures for unknown data sets, and routine applications are primarily associated with fixed logic functions, which may be preliminarily designed and do not need frequent modifications, e.g., the vocabulary structure. But for further design, one should analyze restrictions, possibly for run time. Also, the actual task is to use parallel process schemes for calculations of fragmented large-scale multi-parametric functions. Additionally, that is the motive to design prospective quantum computing schemes for the minimization of functions with a very large number of input variables. The second restriction is determined by the fact that now AGA (as any other purely logic calculus) does not have any internal tools for robotic WM design and optimization tasks, and all necessary knowledge should be taken from external sources and expert knowledge. AGA provides a basic learning scheme, with a \"teacher\" that chooses logic constants in the truth table, and that is the reason to consider more complicated heterogeneous logic architecture of agents [75]. Also, that leads to the necessity of taking into account the basic scheme of the agent (like the one shown in Figure 9) and its set of variables. Otherwise, the excessive vocabulary structure is to be worked out, and it can reduce the efficiency and the possible gain from the application of AGA. One more actual limitation for verification systems and AGA modeling of agents is the specifics of robotic computer vision systems [13; 14] based on NN. Now, such systems [13; 14; 66] can unhurriedly recognize components of real scenes of action, and they cannot detect illegal physical activity of cheaters and rival robots. At the same time, computer systems demonstrate real success in fake-image generation [90], thus drastically raising the requirement for verification methods in such extensively developing fields as IoV and the positioning of delivery drones. But verification procedures need monitoring of images of cargo, terminals, territorial restrictions, and face control data. And the lack of computer vision blocks the advantage of AGA systems to manually correct the multi-parametric template for an actual event or object. More local limitations can also occur due to the high cost of QRNG modules and the necessity of involving high-quality cryptographic hash functions [91] for data protection procedures in mass robotics. Here, the real expenses will depend on the output volume of such components.