The field of game theory and algorithmic techniques is witnessing significant developments, with a focus on improving the efficiency and accuracy of existing methods. Researchers are exploring new approaches to tackle complex problems in stochastic games, network games, and extensive-form games. One notable direction is the development of novel algorithms for computing Nash equilibria and perfect equilibria in various types of games. Additionally, there is a growing interest in applying game-theoretic concepts to real-world problems, such as participatory budgeting and voting systems. Noteworthy papers in this area include: The paper on widest path games and maximality inheritance in bounded value iteration for stochastic games, which presents a clean BVI algorithm based on widest path games and proves its correctness using the maximality inheritance principle. The paper on solving Pasur using GPU-accelerated counterfactual regret minimization, which introduces a CUDA-accelerated computational framework for simulating Pasur and computing near-Nash equilibria via counterfactual regret minimization.