{"title":"Time-Critical Decision Making in Interactive Dynamic Influence Diagram","authors":"Yi-feng Zeng, Yanping Xiang","doi":"10.1109/WI-IAT.2010.82","DOIUrl":null,"url":null,"abstract":"Time-critical dynamic decision making is a quite challenging task in many real-world applications. It requires to play a trade-off between solution optimality and computational tractability. It is especially true for multiagent settings under uncertainty. In this paper, we model time-critical dynamic decision problem using the representation of interactive dynamic influence diagram~(I-DID). We formalize I-DID by providing time-index to nodes within the model. This results in a model that has the ability to represent space-temporal abstraction. In addition, we propose a new method for selecting the abstract model without arbitrarily compromising solution optimality. We evaluate the performance of our method in two benchmark settings and provide results in support.","PeriodicalId":123634,"journal":{"name":"ACM International Conference on International Agent Technology","volume":"202 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM International Conference on International Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2010.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Time-critical dynamic decision making is a quite challenging task in many real-world applications. It requires to play a trade-off between solution optimality and computational tractability. It is especially true for multiagent settings under uncertainty. In this paper, we model time-critical dynamic decision problem using the representation of interactive dynamic influence diagram~(I-DID). We formalize I-DID by providing time-index to nodes within the model. This results in a model that has the ability to represent space-temporal abstraction. In addition, we propose a new method for selecting the abstract model without arbitrarily compromising solution optimality. We evaluate the performance of our method in two benchmark settings and provide results in support.