MultiStyle: Characterizing Multiplayer Cooperative Gameplay by Incorporating Distinct Player Playstyles in a Multi-Agent Planner

Eric W. Lang, R. Michael Young
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Abstract

This paper presents MultiStyle, a multi-agent centralized heuristic search planner that incorporates distinct agent playstyles to generate solution plans where characters express individual preferences while cooperating to reach a goal. We include algorithmic details, an example domain, and multiple different solution plans generated with unique agent playstyle sets. We discuss our intent to incorporate this planner in a tool for game level designers to help them anticipate and understand how teams of players with distinct playstyles may play through their levels. Ultimately, MultiStyle generates solution plans with a novel and increased expressive range by attempting to satisfy sets of action and proposition preferences for each agent.
MultiStyle:通过在Multi-Agent Planner中整合不同的玩家游戏风格来描述多人合作游戏玩法
本文介绍了MultiStyle,这是一个多智能体集中式启发式搜索规划器,它结合了不同的智能体游戏风格来生成解决方案,其中角色在合作达到目标的同时表达个人偏好。我们包含了算法细节,一个示例域,以及由独特的代理游戏风格集生成的多个不同的解决方案。我们打算将这个计划整合到游戏关卡设计师的工具中,帮助他们预测和理解具有不同游戏风格的玩家团队如何通关。最终,MultiStyle通过尝试满足每个智能体的动作和命题偏好集,生成具有新颖和更大表达范围的解决方案计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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