{"type":"ScholarlyArticle","title":"Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations","authors":[{"name":"Joseph Kim","slug":"joseph-kim","given":"Joseph","family":"Kim","affiliation":"MIT Computer Science and Artificial Intelligence Laboratory"},{"name":"Christian Muise","slug":"christian-muise","given":"Christian","family":"Muise","affiliation":"MIT-IBM Watson AI Lab"},{"name":"Ankit Shah","slug":"ankit-shah","given":"Ankit","family":"Shah","affiliation":"MIT Computer Science and Artificial Intelligence Laboratory"},{"name":"Shubham Agarwal","slug":"shubham-agarwal","given":"Shubham","family":"Agarwal","affiliation":"MIT-IBM Watson AI Lab"},{"name":"Julie Shah","slug":"julie-shah","given":"Julie","family":"Shah","affiliation":"MIT Computer Science and Artificial Intelligence Laboratory"}],"abstract":"Temporal logics are useful for providing concise descriptions of system behavior, and have been successfully used as a language for goal definitions in task planning. Prior works on inferring temporal logic specifications have focused on \"summarizing\" the input dataset - i.e., finding specifications that are satisfied by all plan traces belonging to the given set. In this paper, we examine the problem of inferring specifications that describe temporal differences between two sets of plan traces. We formalize the concept of providing such contrastive explanations, then present BayesLTL - a Bayesian probabilistic model for inferring contrastive explanations as linear temporal logic (LTL) specifications. We demonstrate the robustness and scalability of our model for inferring accurate specifications from noisy data and across various benchmark planning domains.","doi":"10.24963/ijcai.2019/776","url":"https://ijcai.org/proceedings/2019/776","pdf":"https://ijcai.org/proceedings/2019/0776.pdf","markdown":"https://ijcai.org/proceedings/2019/776.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/776","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Planning and Scheduling","track":"Main track","number":776,"pages":{"first":5591,"last":5598},"keywords":["Planning and Scheduling: Search in Planning and Scheduling","Planning and Scheduling: Activity and Plan Recognition","Humans and AI: Human-AI Collaboration"],"videos":[],"references":[{"position":1,"raw":"[Anastasiou, 2006] Alexander B Anastasiou. 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