multi-agent systems

This paper proposes a novel architecture of a multi-agent system and its formal specification for analyzing and adaptively correcting students' learning trajectories using software agents in digital learning environments. The proposed approach integrates artificial intelligence tools, tem- poral logic, and a multi-agent system architecture to ensure personalized adaptation of educational content.

The game model of multi-agent systems of self-organizing in the conditions of uncertainty is developed. The formulation of a stochastic game problem is carried out, criteria of self-organizing of strategies of players are defined, a recurrent method, algorithm and software of learning of multi-agent system to simulate the synchronised rhythmic luminescence of a colony of fireflies are developed.