Historically applied exclusively to perfect information games, depth-limited search with value
functions has been key to recent advances in AI for imperfect information games. Most …

Neuro-symbolic approaches to artificial intelligence, which combine neural networks with
classical symbolic techniques, are growing in prominence, necessitating formal approaches …

Conducting additional search during test time is often used to improve the performance of
reinforcement learning algorithms. Performing search in adversarial games with imperfect …

Limited look-ahead search with a heuristic value function is a key AI technique in
reinforcement learning and game playing. In perfectinformation problems, this has …

Recent advancements in algorithms for sequential decision-making under imperfect
information have shown remarkable success in large games such as limit-and no-limit …