The field of autonomous systems and energy communities is witnessing a significant shift towards cooperative game theory, enabling more efficient and adaptive decision-making. Recent developments have focused on designing frameworks that incorporate human intent, autonomy, and decentralized communication mechanisms to improve overall system performance. Notably, the integration of game-theoretic approaches has led to the development of novel strategies for shared autonomy, human-in-the-loop learning, and demand response in smart grids. These advancements have the potential to enhance the scalability, stability, and efficiency of complex systems. Noteworthy papers include: Flip Co-op, which develops a game-theoretic framework for cooperative takeover in shared autonomy, providing analytical insights and efficient computation of cooperative takeover policies. Private Markovian Equilibrium in Stackelberg Markov Games for Smart Grid Demand Response, which introduces private Markovian strategies and equilibrium, enabling the computation of equilibrium in polynomial time. Human-in-the-loop Learning Through Decentralized Communication Mechanisms, which proposes a decentralized communication mechanism to regulate human-in-the-loop learning against selfish agents' free-riding, demonstrating its effectiveness in simulation experiments.