Epistemic specifications and conformant planning

Yan Zhang, Yuanlin Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Epistcmic Specifications allow for the correct representation of incomplete information in the presence of multiple belief sets by expanding Answer Set Programming with modal operators K and M. The meaning of M in the existing work does not correspond well to the principle of justifiedness accepted by the community. It is, however, challenging to characterize the justfiedness of each belief, due to the complexity introduced by M. We address this issue by identifying a belief set with a program which uniquely decides the belief set. This idea leads to a novel definition of the semantics of Epistemic Specifications which assures that each belief in any belief set is well justified. We also show that conformant planning problems can be naturally represented by Epistemic Specification under our semantics.

Original languageEnglish
Title of host publicationWS-17-01
Subtitle of host publicationArtificial Intelligence and Operations Research for Social Good; WS-17-02: Artificial Intelligence, Ethics, and Society; WS-17-03: Artificial Intelligence for Connected and Automated Vehicles; WS-17-04: Artificial Intelligence for Cyber Security; WS-17-05: Artificial Intelligence for Smart Grids and Buildings; WS-17-06: Computer Poker and Imperfect Information Games; WS-17-07: Crowdsourcing, Deep Learning and Artificial Intelligence Agents; WS-17-08: Distributed Machine Learning; WS-17-09: Joint Workshop on Health Intelligence; WS-17-10: Human-Aware Artificial Intelligence; WS-17-11: Human-Machine Collaborative Learning; WS-17-12: Knowledge-Based Techniques for Problem Solving and Reasoning; WS-17-13: Plan, Activity, and Intent Recognition; WS-17-14: Symbolic Inference and Optimization; WS-17-15: What's Next for AI in Games?
PublisherAI Access Foundation
Pages781-787
Number of pages7
ISBN (Electronic)9781577357865
StatePublished - 2017
Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
Duration: Feb 4 2017Feb 10 2017

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-17-01 - WS-17-15

Conference

Conference31st AAAI Conference on Artificial Intelligence, AAAI 2017
CountryUnited States
CitySan Francisco
Period02/4/1702/10/17

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