两个具有快速策略的多重平行搜索的隐藏搜索游戏

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2022-01-01 DOI:10.1515/comp-2022-0243
P. Creasey
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引用次数: 0

摘要

摘要从N N个不等值的选择中快速做出不可预测的决策是一项常见的控制任务。当可预测性成本可以被智能对手建模为隐藏在单个选项下的惩罚时,则可以使用Sakaguchi描述的零和隐藏搜索游戏的方法,在O(N log N)O\left(N\log N)步骤中有效地找到最优策略。在这项工作中,我们将其扩展到具有多个平行预测的两个游戏,无论是协调的还是独立于最优分布绘制的,这两个游戏都可以用相同的比例求解。开源代码在线提供,网址为https://github.com/pec27/rams.
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Two hide-search games with rapid strategies for multiple parallel searches
Abstract Making a rapid unpredictable decision from N N choices of unequal value is a common control task. When the cost of predictability can be modelled as a penalty hidden under a single option by an intelligent adversary, then an optimal strategy can be found efficiently in O ( N log N ) O\left(N\log N) steps using an approach described by Sakaguchi for a zero-sum hide-search game. In this work, we extend this to two games with multiple parallel predictions, either coordinated or drawn independently from the optimal distribution, both of which can be solved with the same scaling. An open-source code is provided online at https://github.com/pec27/rams.
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来源期刊
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
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