Cooperative robotics in system-informational culture ergonomics

Vasilyev  NS

doi:10.15406/iratj.2025.11.00296

eISSN: 2574-8092

International Robotics & Automation Journal

Opinion Volume 11 Issue 1

Cooperative robotics in system-informational culture ergonomics

Vasilyev NS

Department of Fundamental Sciences, Bauman Moscow State Technical University, Russia

Correspondence:

Received: April 14, 2025 | Published: May 1, 2025

Citation: Vasilyev NS. Cooperative robotics in system-informational culture ergonomics. Int Rob Auto J. 2025;11(1):25-26. DOI: 10.15406/iratj.2025.11.00296

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Abstract

Artificial intelligence penetrates into all spheres of the system-informational culture ergonomics. Robotics universality can be accomplished in the paradigm of cooperative approach and artificial intelligence usage. Intellectual robots can make decisions autonomously. Distributive control in the cooperative system of robots allows to find optimal solution of the needed scheduling problem. The relational game theoretical approach is to be used for robots’ simulation. Instead of the traditional games problem formulation, relational form has to be applied. This reduces the dimension of the tasks solved. Cooperation is based on messaging through communications network. Its choice becomes the essential part of players’ decisions making based on the application of the game principles of equilibrium and effectiveness.

Keywords: multiagent system, intelligent player, relational game, coalition, communications network, scheduling problem, category of binary relations; preferences, precedence, capabilities, opportunities relations

Introduction

In the ergonomics of the up-to-date system-informational culture there is a trend of artificial intelligence increasing usage.¹ The trend is also observed in robotics. A new technology of robots’ team self-organization is expected to appear. In the article, robots’ cooperation is simulated by means of multiagent systems (MAS) study. Intellectual agents are quite capable to process incoming information and make independent decisions. The game theoretical approach can be applied to cooperative robotics development.

The traditional game problem statement will have to be abandoned.² Firstly, the choice of players’ payment functions in applications raises many questions. Secondly, the number of pairwise different game situations increases exponentially with the number of players. In my opinion, the game must be stated in the form of relations.^3,4 Situations of the game are different game completion options. On their set agents’ interests can be represented with the help of preferences relations. Players’ capabilities can be also expressed in comparative form. The approach significantly widens the sphere of games applications⁵ and diminishes the dimension of the solved problem.

As for robots’ cooperation, their aim is to provide a set of tasks which is also preordered by means of a precedence relation. The agents have to compete to choice the most suitable tasks for them. In order to do it, they lean on their preferences relations and consider heterogeneous capabilities of their partners. Decision making uncertainty forces them to cooperate by means of messaging. Communications network choice becomes the essential part of the players’ cooperative behavior. They can apply acceptable strategies depending on their awareness provided by the exchange of information.²⁻⁴ The players have to find the optimal tasks scheduling⁶ which is to be stable. It is required to find solution of the game based on the equilibrium and effectiveness principles.² In the relational game it can be achieved with the help of a polynomial algorithm.

Problem formulation

Category of binary relations⁷ suits to the aims of MAS simulation in the most general terms. Allow robots’ preferences relations be given on the set of all tasks to be provided. The tasks are to be completed according to the ordering according to the given precedence relation The smallest elements of the preordered set cannot be at all accomplished by robot Every task is to be fulfilled only by one of the robots. Capabilities of the agents are compared with the help of the given relationship Property means that robot makes the task better than robot

The precedence relation defines dynamics of the game. The latter can be divided in series of static subgames where executed tasks do not connected by relation .⁴ In each of them, situations are partial schedules. By their strategies, players can influence the implementation of certain scheduling scenarios The possibility is also expressed in the comparative form of the players opportunities relationship If the property takes place, player has more influence on the schedule realization than robot In all static subgames, players use messaging to form coalitions. Their aim is to come, if possible, to the optimal partial scenario It means, the task from the scenario may be executed by robot Coalitions are to be created by agents themselves. For the purpose, intelligent robots are able to use the set of relations to find effective hierarchical and parallel coalitions.^3,4 In this way, optimal communications network emerges which makes players’ moves preordered. Due to it, every coalition picks out the set of tasks to be provided. The tasks can be reassigned among partners to achieve Pareto optimal scheduling.⁸ For the purpose, relationship is used.

Cooperative scheduling

Distributed control in the system is coordinated by messaging. Robots inform each other about tasks they chose to provide. As coalitions are formed, any static subgames is to be reduced. Coalitions have their own strategies intended for the scheduling optimization leaning on their preferences relations termed characteristic ones.³ Every coalition is regarded on as a player in the reduced game. The relations are compositions of initial robots’ preferences relations built with the help of the following monoidal operations. They are relations disjunctive sum and superposition correspondingly.⁷

Example 1 Parallel and hierarchical coalitions, made up of coalitions previously formed, have the following characteristic relations:³

This is how all coalitions are built.

Applying relational Bellman’s method to the scale dynamic relationships are built.⁴ The equilibrium scheduling is found as solution of the problem Here, the game resulting relation is characteristic relation of the whole dynamic game.⁴

Conclusion

In the system-informational culture artificial intelligence develops human tools. Intellectual robots’ cooperation allows solving effectively relational scheduling problem. Future technology consists of relational approach application. Intellectual robots’ cooperation engenders a distributive scheduling method through the communications network chosen by them. The algorithm has polynomial complexity. This is a general trend in the development of intellectual multiagent systems.