The field of game theory and optimization is witnessing significant developments, with a focus on improving algorithms and understanding complex game dynamics. Researchers are exploring new approaches to solve classic problems, such as the traveling tournament problem and split-delivery routing problems, with a emphasis on finding efficient and optimal solutions. The study of simultaneous best-response dynamics in random potential games has also led to new insights into the convergence behavior of these systems. Additionally, the development of new algorithms, such as Generational Adversarial MAP-Elites, is enabling the illumination of adversarial multi-agent games and opening up new avenues for research. Noteworthy papers include: Adversarial Coevolutionary Illumination with Generational Adversarial MAP-Elites, which proposes a new algorithm for coevolving solutions in adversarial games. Study and improvement of search algorithms in two-players perfect information games, which introduces a new search algorithm that outperforms existing ones in a large experiment.