Versatile Uncertainty Quantification of Contrastive Behaviors for Modeling Networked Anagram Games
Versatile Uncertainty Quantification of Contrastive Behaviors for Modeling Networked Anagram Games
复制标题
用于网络化 Anagram 游戏建模的对比行为的多功能不确定性量化
DOI:
10.1007/978-3-030-93409-5_53
复制
发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Kuhlman, Chris J
中科院分区:
文献类型:
--
作者:
Hu, Zhihao;Deng, Xinwei;Kuhlman, Chris J
In a networked anagram game, each team member is given a set of letters and members collectively form as many words as possible. They can share letters through a communication network in assisting their neighbors in forming words. There is variability in behaviors of players, e.g., there can be large differences in numbers of letter requests, of replies to letter requests, and of words formed among players. Therefore, it is of great importance to understand uncertainty and variability in player behaviors. In this work, we propose versatile uncertainty quantification (VUQ) of behaviors for modeling the networked anagram game. Specifically, the proposed methods focus on building contrastive models of game player behaviors that quantify player actions in terms of worst, average, and best performance. Moreover, we construct agent-based models and perform agent-based simulations using these VUQ methods to evaluate the model building methodology and understand the impact of uncertainty. We believe that this approach is applicable to other networked games.
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发表时间:
2021
期刊:
International Workshop on Complex Networks & Their Applications
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