Recent research in game theory-based task scheduling in cloud computing focuses on optimizing the allocation and execution of tasks by modeling the interactions between cloud users and service providers as strategic games. Game-theoretic approaches such as non-cooperative, cooperative, and Stackelberg games are applied to balance objectives like energy efficiency, task completion time, cost, and fairness. These methods enable autonomous decision-making where each participant aims to maximize its utility while maintaining overall system equilibrium. By integrating game theory with resource scheduling algorithms, researchers have developed dynamic, adaptive, and incentive-compatible frameworks that enhance performance, minimize conflicts, and ensure efficient utilization of cloud resources.