{"type":"ScholarlyArticle","title":"The Emerging Landscape of Explainable Automated Planning & Decision Making","authors":[{"name":"Tathagata Chakraborti","slug":"tathagata-chakraborti","given":"Tathagata","family":"Chakraborti","affiliation":"IBM Research AI"},{"name":"Sarath Sreedharan","slug":"sarath-sreedharan","given":"Sarath","family":"Sreedharan","affiliation":"Arizona State University"},{"name":"Subbarao Kambhampati","slug":"subbarao-kambhampati","given":"Subbarao","family":"Kambhampati","affiliation":"Arizona State University"}],"abstract":"In this paper, we provide a comprehensive outline of the different threads of work in Explainable AI Planning (XAIP) that has emerged as a focus area in the last couple of years and contrast that with earlier efforts in the field in terms of techniques, target users, and delivery mechanisms. We hope that the survey will provide guidance to new researchers in automated planning towards the role of explanations in the effective design of human-in-the-loop systems, as well as provide the established researcher with some perspective on the evolution of the exciting world of explainable planning.","doi":"10.24963/ijcai.2020/669","url":"https://ijcai.org/proceedings/2020/669","pdf":"https://ijcai.org/proceedings/2020/0669.pdf","markdown":"https://ijcai.org/proceedings/2020/669.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/669","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Survey track","track":"Survey track","number":669,"pages":{"first":4803,"last":4811},"keywords":["Planning and Scheduling: general","Safe, Explainable, and Trustworthy AI: general","Human aspects in AI: general"],"videos":[],"references":[{"position":1,"raw":"Explanation Type Social Contrastive Selective Local Global Abstraction User Study Algorithm-based explanations [37; 2] [37; 27; 44; 2; 36] [37; 27; 51; 44; 2; 36] [] [27; 51;","title":"Explanation Type Social Contrastive Selective Local Global Abstraction User Study Algorithm-based explanations","authors":null,"year":null,"venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"Model-Based Explanations Inference Reconciliation [72; 74; 20; 69; 50; 37; 81; 76; 2] [63; 4; 72; 74; 20; 69; 25; 41; 19; 22; 50; 37; 7; 84; 83; 76; 81; 57; 1; 2; 88] [27; 63; 4; 72; 74; 20; 69; 25; 41; 19; 50; 37; 83; 36] [63; 27; 4; 72; 74; 20; 69; 25; 41; 19; 22; 50; 37; 7; 84; 83; 76; 81; 36; 57; 1; 78; 2; 88] [74; 20; 69; 25] [72; 74; 20; 69; 41; 50; 81; 76] [4; 27; 74; 41; 19; 50; 84; 76; 81; 57; 2] Model Reconciliation [15; 72; 74; 69; 71; 70; 13; 68; 8; 79; 10; 56] [15; 72; 74; 69; 71; 70; 13; 68; 8; 79; 10; 56] [15; 72; 74; 69; 71; 70; 13; 68; 8; 79; 10; 56] [15; 72; 71; 70; 13; 68; 8] [15; 74; 69] [72; 74; 69] [12; 74; 70; 13; Plan-based explanations [47; 8; 61; 33] [85; 44; 73; 77; 33; 47; 43; 8; 61; 78] [85; 44; 73; 77; 33; 47; 43; 8; 61; 38; 80; 39; 78; 16] [85; 44; 73; 77; 33; 61]","title":"Model-Based Explanations Inference Reconciliation","authors":null,"year":null,"venue":"Model-Based Explanations Inference Reconciliation","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"Tobias Ahlbrecht and Michael Winikoff. 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