Xudong Luo , Yanling Li , Qiaojuan Huang , Jieyu Zhan
{"title":"自动谈判调查:人为因素、学习和应用","authors":"Xudong Luo , Yanling Li , Qiaojuan Huang , Jieyu Zhan","doi":"10.1016/j.cosrev.2024.100683","DOIUrl":null,"url":null,"abstract":"<div><div>The burgeoning field of automated negotiation systems represents a transformative approach to resolving conflicts and allocating resources with enhanced efficiency. This paper presents a thorough survey of this discipline, emphasising the implications of human factors, the application of machine learning techniques, and the real-world deployments of these systems. In traditional manual negotiation, various challenges emerge, including limited negotiation skills, power asymmetries, personality disparities, and cultural influences. Automated negotiation systems can offer solutions to these challenges through their round-the-clock availability, the ability to negotiate without emotional bias, efficient information access, and seamless integration of cultural contexts. This comprehensive survey delves into the intricacies of human–computer negotiation, shedding light on the impact of emotional cues, cultural diversity, and the subtleties of language. Furthermore, the study reviews the incorporation of machine learning models that facilitate the adaptation of negotiation strategies. The paper also discusses the application of fuzzy set theory and fuzzy constraint methods within the scope of automated negotiation, providing a valuable addition to the existing literature. Real-world deployment of these systems in domains e.g., e-commerce, conflict resolution, and multi-agent systems is also examined. By providing a broad overview of automated negotiation, this survey acknowledges the vital role of human factors in negotiation processes, underscores the value of intelligent and adaptive negotiation techniques and offers valuable insights into the practical applications of these systems in various real-world contexts.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":null,"pages":null},"PeriodicalIF":13.3000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A survey of automated negotiation: Human factor, learning, and application\",\"authors\":\"Xudong Luo , Yanling Li , Qiaojuan Huang , Jieyu Zhan\",\"doi\":\"10.1016/j.cosrev.2024.100683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The burgeoning field of automated negotiation systems represents a transformative approach to resolving conflicts and allocating resources with enhanced efficiency. This paper presents a thorough survey of this discipline, emphasising the implications of human factors, the application of machine learning techniques, and the real-world deployments of these systems. In traditional manual negotiation, various challenges emerge, including limited negotiation skills, power asymmetries, personality disparities, and cultural influences. Automated negotiation systems can offer solutions to these challenges through their round-the-clock availability, the ability to negotiate without emotional bias, efficient information access, and seamless integration of cultural contexts. This comprehensive survey delves into the intricacies of human–computer negotiation, shedding light on the impact of emotional cues, cultural diversity, and the subtleties of language. Furthermore, the study reviews the incorporation of machine learning models that facilitate the adaptation of negotiation strategies. The paper also discusses the application of fuzzy set theory and fuzzy constraint methods within the scope of automated negotiation, providing a valuable addition to the existing literature. Real-world deployment of these systems in domains e.g., e-commerce, conflict resolution, and multi-agent systems is also examined. By providing a broad overview of automated negotiation, this survey acknowledges the vital role of human factors in negotiation processes, underscores the value of intelligent and adaptive negotiation techniques and offers valuable insights into the practical applications of these systems in various real-world contexts.</div></div>\",\"PeriodicalId\":48633,\"journal\":{\"name\":\"Computer Science Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":13.3000,\"publicationDate\":\"2024-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science Review\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1574013724000674\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science Review","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574013724000674","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A survey of automated negotiation: Human factor, learning, and application
The burgeoning field of automated negotiation systems represents a transformative approach to resolving conflicts and allocating resources with enhanced efficiency. This paper presents a thorough survey of this discipline, emphasising the implications of human factors, the application of machine learning techniques, and the real-world deployments of these systems. In traditional manual negotiation, various challenges emerge, including limited negotiation skills, power asymmetries, personality disparities, and cultural influences. Automated negotiation systems can offer solutions to these challenges through their round-the-clock availability, the ability to negotiate without emotional bias, efficient information access, and seamless integration of cultural contexts. This comprehensive survey delves into the intricacies of human–computer negotiation, shedding light on the impact of emotional cues, cultural diversity, and the subtleties of language. Furthermore, the study reviews the incorporation of machine learning models that facilitate the adaptation of negotiation strategies. The paper also discusses the application of fuzzy set theory and fuzzy constraint methods within the scope of automated negotiation, providing a valuable addition to the existing literature. Real-world deployment of these systems in domains e.g., e-commerce, conflict resolution, and multi-agent systems is also examined. By providing a broad overview of automated negotiation, this survey acknowledges the vital role of human factors in negotiation processes, underscores the value of intelligent and adaptive negotiation techniques and offers valuable insights into the practical applications of these systems in various real-world contexts.
期刊介绍:
Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.