The recent developments in the research area of game theory and resource allocation have seen significant advancements in understanding and solving complex strategic interactions. Researchers are focusing on extending classic models like the Colonel Blotto game to include more realistic elements such as costs and elasticity parameters, which influence the computational complexity of finding Nash equilibria. These extensions not only provide deeper insights into the equilibrium behavior but also offer efficient algorithms for practical applications in security, auditing, and elections. Additionally, the study of Tullock contests has revealed new complexity results, distinguishing scenarios where efficient algorithms can be designed from those that remain computationally hard. The exploration of oracle complexity in matrix games has further delineated the boundaries of computational feasibility, with notable improvements in lower bounds for approximating Nash equilibria. Overall, the field is progressing towards more nuanced and computationally tractable models, enhancing our ability to analyze and predict strategic outcomes in various domains.