This paper presents a new AI challenge, the Tales of Tribute AI Competition
(TOTAIC), based on a two-player deck-building card game released with the High
Isle chapter of The Elder Scrolls Online. Currently, there is no other AI
competition covering Collectible Card Games (CCG) genre, and there has never
been one that targets a deck-building game. Thus, apart from usual CCG-related
obstacles to overcome, like randomness, hidden information, and large branching
factor, the successful approach additionally requires long-term planning and
versatility. The game can be tackled with multiple approaches, including
classic adversarial search, single-player planning, and Neural Networks-based
algorithms. This paper introduces the competition framework, describes the
rules of the game, and presents the results of a tournament between sample AI
agents. The first edition of TOTAIC is hosted at the IEEE Conference on Games
2023.

本文介绍了一项基于《上古卷轴》中的双人卡牌游戏的 AI 挑战赛，目标在于开发应对随机性、信息不对称、策略多样等多种挑战的 AI 算法，该比赛旨在鼓励使用经典对抗搜索、单人策略规划和神经网络等多种算法进行游戏策略实现，是 CCG 领域中首次针对卡组构筑的 AI 挑战赛。

介绍致敬 AI 比赛

Introducing Tales of Tribute AI Competition

Monte-Carlo Tree Search (MCTS) is an adversarial search paradigm that first
found prominence with its success in the domain of computer Go. Early
theoretical work established the game-theoretic soundness and convergence
bounds for Upper Confidence bounds applied to Trees (UCT), the most popular
instantiation of MCTS; however, there remain notable gaps in our understanding
of how UCT behaves in practice. In this work, we address one such gap by
considering the question of whether UCT can exhibit lookahead pathology -- a
paradoxical phenomenon first observed in Minimax search where greater search
effort leads to worse decision-making. We introduce a novel family of synthetic
games that offer rich modeling possibilities while remaining amenable to
mathematical analysis. Our theoretical and experimental results suggest that
UCT is indeed susceptible to pathological behavior in a range of games drawn
from this family.

本研究通过引入一种新的合成游戏家族，从理论和实验两个方面研究了 UCT 算法的前瞻病理学，表明 UCT 算法在一些游戏中存在病理行为。