While Poker, as a family of games, has been studied extensively in the last
decades, collectible card games have seen relatively little attention. Only
recently have we seen an agent that can compete with professional human players
in Hearthstone, one of the most popular collectible card games. Although
artificial agents must be able to work with imperfect information in both of
these genres, collectible card games pose another set of distinct challenges.
Unlike in many poker variants, agents must deal with state space so vast that
even enumerating all states consistent with the agent's beliefs is intractable,
rendering the current search methods unusable and requiring the agents to opt
for other techniques. In this paper, we investigate the strength of such
techniques for this class of games. Namely, we present preliminary analysis
results of ByteRL, the state-of-the-art agent in Legends of Code and Magic and
Hearthstone. Although ByteRL beat a top-10 Hearthstone player from China, we
show that its play in Legends of Code and Magic is highly exploitable.

通过对 ByteRL 在《法典传说》和《炉石传说》中的表现进行初步分析，我们发现这种技术在这类游戏中的可利用性很高。

学习击败 ByteRL：可收集卡牌游戏智能体的可利用性

Learning to Beat ByteRL: Exploitability of Collectible Card Game Agents

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。