论文标题
训练刺客人工智能以阻力：阿瓦隆
Training an Assassin AI for The Resistance: Avalon
论文作者
论文摘要
阻力：阿瓦隆是一部可观察到的社会推论游戏。 AI游戏的这一领域还没有开发。为该游戏实施AI涉及每个阶段特定的多个组件以及在游戏中的角色。在本文中，我们计划通过首先解决暗杀阶段来迭代为每个角色/阶段开发所需的组件，该阶段可以建模为机器学习问题。使用游戏的在线版本中的公开数据集，我们训练模仿刺客的分类器。在尝试了各种分类技术之后，我们能够使用简单的线性支持向量分类器实现高于平均水平的人类绩效。该项目的最终目标是追求一个聪明而完整的Avalon玩家，可以在游戏的每个阶段中扮演任何角色。
The Resistance: Avalon is a partially observable social deduction game. This area of AI game playing is fairly undeveloped. Implementing an AI for this game involves multiple components specific to each phase as well as role in the game. In this paper, we plan to iteratively develop the required components for each role/phase by first addressing the Assassination phase which can be modeled as a machine learning problem. Using a publicly available dataset from an online version of the game, we train classifiers that emulate an Assassin. After trying various classification techniques, we are able to achieve above average human performance using a simple linear support vector classifier. The eventual goal of this project is to pursue developing an intelligent and complete Avalon player that can play through each phase of the game as any role.
