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

Technical faults, attacks, and illegal data modification make distant data verification the obligatory component of collective robotic systems. In order to design comprehensive verification procedures for scalable collectives of agents, the presented paper proposes multiple-valued AGA model and the protocol of agents' communications, based on ordered vocabulary structure, formal logic language, and the adapted LL scheme. The verification procedure is considered to consist of a set of data integrity and authentication tests activated for the initial debugging of the agent, periodical testing, work correction, and system restoration. Verification procedures can be initiated by a distant administrator, a partner robot from the same MAS, the state regulator's agents, and external robots. Verification tasks motivate us to combine automatic and manual checks, to use non-exhausted selective check procedures, and to involve distributed LL local data storages for critical data documenting. AGA data coding and data verification methods are expected to complement other known data protection methods and schemes, preventing illegal data modifications. The presented materials follow the known methodology of cryptography and data leakage-protection systems for the clear analysis of basic models. They should be initially disclosed for common access and public search of vulnerabilities. The designed basic protocols and procedures are presented for common discussion at the early enough stage, with partial technical realization. The proposed AGA methods are, in essence, clear for such analysis due to the very structure of AGA logic calculations. The choice of discrete AGA calculus is determined by the possibility of easily obtaining high-dimensional and multi-parametrical space [26; 75], describing the scalable scene of action and agents. Necessary precision of data representation and wide bands for time and space parameters is proposed to be provided by the scheme of correlated input logic variables. In the presented method, verification procedures combine several components:

* AGA logic modeling of communications in a large-scale robotic system;
* The proposed three-level ordered vocabulary structure, describing terminology for agents and the scene of action by coded words and collocations, represented by subsets given simultaneously in the natural language, \(V^{L}\); natural-number codes, \(V^{N}\); and truth-level codes, \(V^{K}\);
* The designed logic protocol of phrase formation and process, using equal 8-byte headers and content parts;
* Distributed data storages in participating agents are proposed to use the adapted version of LL, providing the mixing of logic notations for 8-bit platforms. Proposed tools are attributed to verification tasks of autonomous agents, requesting authentication parameters of other agents. Phrase processin in dialog procedures is based on the calculation of AGA functions and does not disclose real physical values of coded internal parameters. The advantage of the designed method is the content-based access to data storage, using the natural-number code or randomly assigned hashes as access keys. Phrases in dialogs of robots can be transmitted by parts due to the designed algorithm and software, capable of checking the integrity of phrases, combined logic calculations, and traditional arithmetic procedures. The first proposed scheme gives the possibility to obtain small dimensional (1D, 2D, and 3D) fragmented projections (or logic diagrams) by mapping of multi-parametric logic AGA functions onto truth-level scale. This method is applicable both for human and automatic verification procedures. The dialog protocols of logic phrase and components of the coded vocabulary structure were supported by algorithms and software modeling; logic phrase processin and dataextraction from the adapted LL were demonstrated by two microassembler subroutines. Subroutine LLWRD has realized the algorithm for logic data extraction from the proposed adapted version of the LL module.