{"type":"ScholarlyArticle","title":"Evidential Reasoning and Learning: a Survey","authors":[{"name":"Federico Cerutti","slug":"federico-cerutti","given":"Federico","family":"Cerutti","affiliation":"University of Brescia , Italy; Cardiff University , UK"},{"name":"Lance M. Kaplan","slug":"lance-m-kaplan","given":"Lance M.","family":"Kaplan","affiliation":"US DEVCOM ARL , USA"},{"name":"Murat Şensoy","slug":"murat-sensoy","given":"Murat","family":"Şensoy","affiliation":"Amazon , Alexa AI , London , UK"}],"abstract":"When collaborating with an artificial intelligence (AI) system, we need to assess when to trust its recommendations. Suppose we mistakenly trust it in regions where it is likely to err. In that case, catastrophic failures may occur, hence the need for Bayesian approaches for reasoning and learning to determine the confidence (or epistemic uncertainty) in the probabilities of the queried outcome. Pure Bayesian methods, however, suffer from high computational costs. To overcome them, we revert to efficient and effective approximations. In this paper, we focus on techniques that take the name of evidential reasoning and learning from the process of Bayesian update of given hypotheses based on additional evidence. This paper provides the reader with a gentle introduction to the area of investigation, the up-to-date research outcomes, and the open questions still left unanswered.","doi":"10.24963/ijcai.2022/760","url":"https://ijcai.org/proceedings/2022/760","pdf":"https://ijcai.org/proceedings/2022/0760.pdf","markdown":"https://ijcai.org/proceedings/2022/760.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/760","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Survey Track","track":"Survey Track","number":760,"pages":{"first":5418,"last":5425},"keywords":["Survey Track: Uncertainty in AI","Survey Track: Machine Learning","Survey Track: Knowledge Representation and Reasoning","Survey Track: -"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38987313","length_sec":72,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985456","length_sec":668,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Abdar et al., 2021] M. 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