Multi-agent interaction and nonlinear Markov games
Vassili N. Kolokoltsov, Oleg A. Malafeyev

TL;DR
This paper models multi-agent interactions in large populations using nonlinear Markov games, focusing on how major players influence the collective behavior of many small agents under various control and resistance scenarios.
Contribution
It introduces a framework for analyzing large-scale multi-agent systems with major and minor players, incorporating evolutionary dynamics and control mechanisms in nonlinear Markov game models.
Findings
Model captures influence of big players on small agents' strategies.
Framework applies to real-world problems like security, regulation, and system management.
Provides insights into coalition formation and system evolution.
Abstract
The general picture of game theoretic modeling dealt with here is characterized by a set of big players, also referred to as principals or major agents, acting on the background of large pools of small players, the impact of the behavior of each small player in a group on the overall evolution decreasing with the increase of the size of the group. In this Part I approach players in groups are not independent rational optimizers. They are either directly controlled by principals and serve the interests of the latter (pressure and collaboration setting) or they resist the actions of the principals (pressure and resistance setting) by evolving their strategies in an 'evolutionary manner' via interactions with other players subject to certain clear rules, deterministic or stochastic. The examples of the real world problems involved include government representatives (often referred to in…
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Taxonomy
TopicsGame Theory and Applications · Opinion Dynamics and Social Influence · Economic theories and models
