Article’s

Game Theory provides a mathematical framework for analysing strategic interactions among rational agents and has found widespread applications in economics, engineering, and network science [37], [2]. In particular, Cooperative Game Theory enables the study of coalition formation and collective behaviour, which is crucial in modelling real-world systems such as social and communication networks [24], [16]. One prominent application is Community Detection, where nodes in a network form group based on shared properties or interactions [1], [5]. However, these problems are computationally complex due to the combinatorial explosion of possible coalitions [16], [35]. This paper explores the foundational principles of game theory, the role of cooperative approaches in community detection, and the computational challenges involved. Furthermore, emerging technologies such as Quantum Computing and Quantum Algorithms are discussed as potential tools to address these challenges [15], [23]. While current hardware limitations persist, ongoing algorithmic advancements demonstrate promising directions for solving complex optimization problems inherent in game-theoretic models [20].