{"title":"联合博弈及其在市场博弈中的应用","authors":"Michel Grabisch , Silvia Lorenzini","doi":"10.1016/j.ijar.2025.109466","DOIUrl":null,"url":null,"abstract":"<div><div>We define Bel coalitional games, that generalize classical coalitional games by introducing uncertainty in the framework. Unlike Bayesian coalitional games, uncertainty is modelled through the Dempster-Shafer theory and every agent can have different knowledge. We propose the notion of contract in our framework, that specifies how agents divide the values of the coalitions and we use the Choquet integral to model the agents' preferences between contracts. In a second step, we define the ex-ante core and the ex-<em>t</em>-interim core, where, in the latter, we need the Dempster conditional rule to update the mass functions of agents. In particular, in the last step of the ex-<em>t</em>-interim case and when the set of states reduces to a singleton, i.e., when there is no uncertainty, we recover the classical definition of the core. We give some conditions for the nonemptiness of the ex-ante and the ex-<em>t</em>-interim core of Bel coalitional games, considering different types of agents' knowledge and different kind of games. Finally, we present Bel market games as an economical application.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"184 ","pages":"Article 109466"},"PeriodicalIF":3.2000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bel coalitional games with application to market games\",\"authors\":\"Michel Grabisch , Silvia Lorenzini\",\"doi\":\"10.1016/j.ijar.2025.109466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We define Bel coalitional games, that generalize classical coalitional games by introducing uncertainty in the framework. Unlike Bayesian coalitional games, uncertainty is modelled through the Dempster-Shafer theory and every agent can have different knowledge. We propose the notion of contract in our framework, that specifies how agents divide the values of the coalitions and we use the Choquet integral to model the agents' preferences between contracts. In a second step, we define the ex-ante core and the ex-<em>t</em>-interim core, where, in the latter, we need the Dempster conditional rule to update the mass functions of agents. In particular, in the last step of the ex-<em>t</em>-interim case and when the set of states reduces to a singleton, i.e., when there is no uncertainty, we recover the classical definition of the core. We give some conditions for the nonemptiness of the ex-ante and the ex-<em>t</em>-interim core of Bel coalitional games, considering different types of agents' knowledge and different kind of games. Finally, we present Bel market games as an economical application.</div></div>\",\"PeriodicalId\":13842,\"journal\":{\"name\":\"International Journal of Approximate Reasoning\",\"volume\":\"184 \",\"pages\":\"Article 109466\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Approximate Reasoning\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0888613X25001070\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Approximate Reasoning","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0888613X25001070","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Bel coalitional games with application to market games
We define Bel coalitional games, that generalize classical coalitional games by introducing uncertainty in the framework. Unlike Bayesian coalitional games, uncertainty is modelled through the Dempster-Shafer theory and every agent can have different knowledge. We propose the notion of contract in our framework, that specifies how agents divide the values of the coalitions and we use the Choquet integral to model the agents' preferences between contracts. In a second step, we define the ex-ante core and the ex-t-interim core, where, in the latter, we need the Dempster conditional rule to update the mass functions of agents. In particular, in the last step of the ex-t-interim case and when the set of states reduces to a singleton, i.e., when there is no uncertainty, we recover the classical definition of the core. We give some conditions for the nonemptiness of the ex-ante and the ex-t-interim core of Bel coalitional games, considering different types of agents' knowledge and different kind of games. Finally, we present Bel market games as an economical application.
期刊介绍:
The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest.
Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning.
Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.