Identifying Belief Sequences in a Network of Communicating Agents
Identifying Belief Sequences in a Network of Communicating Agents
复制标题
识别通信主体网络中的信念序列
DOI：
10.1007/978-3-030-33792-6_23
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Katsumi Inoue
中科院分区：
文献类型：
--
作者：
Gauvain Bourgne;Yutaro Totsuka;Nicolas Schwind;Katsumi Inoue
最近引入了信念修正游戏（BRG）来模拟通信代理网络中信念的动态。在 BRG 中，每个智能体将她的信念表达为命题公式，并根据她熟人的信念进行迭代修改。 BRG 的一个吸引人的特性是每个智能体的信念序列始终是循环的，因此可以有限地表征。然而，识别这样的信念循环是一项艰巨的任务。本文解决了计算问题，并重点关注代理的修订策略基于众所周知的基于多数的合并算子的情况。特别是，我们展示了如何独立于智能体用来表达其信念的命题语言来识别信念序列中的某些进化模式，从而允许对所有可能的信念循环模式进行详尽的搜索。通过进一步识别导致类似信念循环的信念，我们引入算法来减少搜索空间并对任何给定网络中的信念动态进行详尽的分析。
Belief Revision Games (BRGs) were recently introduced to simulate the dynamics of beliefs in a network of communicating agents. In a BRG, each agent expresses her beliefs as a propositional formula, which are iteratively revised according to the beliefs of her acquaintances. An appealing property of BRGs is that the belief sequence of each agent is always cyclic and thus can be finitely characterized. However, identifying such belief cycles is a hard task. This paper addresses the computational issues and focuses on the case where the revision policies of the agents are based on a well-known majority-based merging operator. In particular, we show how some evolution patterns in the belief sequences can be identified independently of the propositional language used by the agents to express their beliefs, allowing an exhaustive search of all possible belief cycle patterns. By further identifying beliefs that lead to similar belief cycles, we introduce algorithms to reduce the search space and perform an exhaustive analysis of the dynamics of beliefs in any given network.
迷失在翻译中：命题逻辑中的语言独立性——应用于信仰改变
影响因子：
14.4
作者：
P. Marquis;Nicolas Schwind
通讯作者：
Nicolas Schwind
影响因子：
5
作者：
Patricia Everaere;S. Konieczny;P. Marquis
通讯作者：
P. Marquis
DA2 合并运算符
影响因子：
14.4
作者：
S. Konieczny;J. Lang;P. Marquis
通讯作者：
P. Marquis