Andrea Cinfrignini , Silvia Lorenzini , Davide Petturiti
{"title":"A two-player newsvendor game with competition on demand under ambiguity","authors":"Andrea Cinfrignini , Silvia Lorenzini , Davide Petturiti","doi":"10.1016/j.ijar.2025.109546","DOIUrl":null,"url":null,"abstract":"<div><div>We deal with a single period two-player newsvendor game where both newsvendors are assumed to be rational and risk-neutral, and to operate under ambiguity. Each newsvendor needs to choose his/her order quantity of the same perishable product, whose global market demand is modeled by a discrete random variable, endowed with a reference probability measure. Furthermore, the global market demand is distributed to newsvendors according to a proportional allocation rule. We model the uncertainty faced by each newsvendor with an individual <em>ϵ</em>-contamination of the reference probability measure, computed with respect to a suitable class of probability measures. The resulting <em>ϵ</em>-contamination model preserves the expected demand under the reference probability and is used to compute the individual lower expected profit as a Choquet expectation. Therefore, the optimization problem of each player reduces to settle the order quantity that maximizes his/her lower expected profit, given the opponent choice, which is a maximin problem. In the resulting game, we prove that a Nash equilibrium always exists, though it may not be unique. Finally, we provide a characterization of Nash equilibria in terms of best response functions.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109546"},"PeriodicalIF":3.0000,"publicationDate":"2025-08-11","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/S0888613X25001872","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}
引用次数: 0
Abstract
We deal with a single period two-player newsvendor game where both newsvendors are assumed to be rational and risk-neutral, and to operate under ambiguity. Each newsvendor needs to choose his/her order quantity of the same perishable product, whose global market demand is modeled by a discrete random variable, endowed with a reference probability measure. Furthermore, the global market demand is distributed to newsvendors according to a proportional allocation rule. We model the uncertainty faced by each newsvendor with an individual ϵ-contamination of the reference probability measure, computed with respect to a suitable class of probability measures. The resulting ϵ-contamination model preserves the expected demand under the reference probability and is used to compute the individual lower expected profit as a Choquet expectation. Therefore, the optimization problem of each player reduces to settle the order quantity that maximizes his/her lower expected profit, given the opponent choice, which is a maximin problem. In the resulting game, we prove that a Nash equilibrium always exists, though it may not be unique. Finally, we provide a characterization of Nash equilibria in terms of best response functions.
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.