S. Sreedharan, Christian Muise, Subbarao Kambhampati
{"title":"概括行动的理由和政策的因果关系","authors":"S. Sreedharan, Christian Muise, Subbarao Kambhampati","doi":"10.1609/icaps.v33i1.27221","DOIUrl":null,"url":null,"abstract":"We revisit two concepts popularly used within the context of classical planning, namely action justification and causal links. While these concepts have come to underpin some of the most popular notions of explanations in classical planning, these notions are restricted to sequential plans. To address this shortcoming, we propose a generalization of these concepts that is applicable to state-action policies. We introduce algorithms that can identify justified actions and causal links contributed by such actions for policies generated for Fully Observable Non-Deterministic (FOND) planning problems. We also present an empirical evaluation that demonstrates the computational characteristics of these algorithms on standard FOND benchmarks.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generalizing Action Justification and Causal Links to Policies\",\"authors\":\"S. Sreedharan, Christian Muise, Subbarao Kambhampati\",\"doi\":\"10.1609/icaps.v33i1.27221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We revisit two concepts popularly used within the context of classical planning, namely action justification and causal links. While these concepts have come to underpin some of the most popular notions of explanations in classical planning, these notions are restricted to sequential plans. To address this shortcoming, we propose a generalization of these concepts that is applicable to state-action policies. We introduce algorithms that can identify justified actions and causal links contributed by such actions for policies generated for Fully Observable Non-Deterministic (FOND) planning problems. We also present an empirical evaluation that demonstrates the computational characteristics of these algorithms on standard FOND benchmarks.\",\"PeriodicalId\":239898,\"journal\":{\"name\":\"International Conference on Automated Planning and Scheduling\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Automated Planning and Scheduling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1609/icaps.v33i1.27221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Automated Planning and Scheduling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1609/icaps.v33i1.27221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalizing Action Justification and Causal Links to Policies
We revisit two concepts popularly used within the context of classical planning, namely action justification and causal links. While these concepts have come to underpin some of the most popular notions of explanations in classical planning, these notions are restricted to sequential plans. To address this shortcoming, we propose a generalization of these concepts that is applicable to state-action policies. We introduce algorithms that can identify justified actions and causal links contributed by such actions for policies generated for Fully Observable Non-Deterministic (FOND) planning problems. We also present an empirical evaluation that demonstrates the computational characteristics of these algorithms on standard FOND benchmarks.