@COMMENT This file was generated by bib2html.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <http://sourceforge.net/users/patstg/>
@COMMENT This file came from Gal A. Kaminka's publication pages at
@COMMENT http://www.cs.biu.ac.il/~galk/publications/
@inproceedings{aaai18,
	author = {Gal A. Kaminka and Mor Vered and Noa Agmon},
title = {Plan Recognition in Continuous Domains},
booktitle = AAAI,
OPTcrossref = {crossref},
OPTkey = {key},
OPTpages = {pages},
year = {2018},
OPTeditor = {editor},
OPTvolume = {volume},
OPTnumber = {number},
OPTseries = {series},
OPTaddress = {address},
OPTmonth = {month},
OPTorganization = {organization},
OPTpublisher = {publisher},
wwwnote = {An earlier version was published in the IJCAI 2017 workshop on Goal Reasoning.},
OPTannote = {annote},
OPTnote = {},
OPTkeywords = {},
abstract = {
Plan  recognition is the task of inferring the  plan of an agent, based
on an incomplete sequence of its observed actions. Previous formulations of plan
recognition commit early to discretizations of the environment and the observed
agent's actions. This leads to reduced recognition accuracy. To address this, we
first provide a formalization of recognition problems which admits continuous
environments, as well as discrete domains. We then show that through
\textit{mirroring}---generalizing plan-recognition by planning---we
can apply continuous-world motion planners in plan recognition.
We provide formal arguments for the usefulness of mirroring, and empirically
evaluate mirroring  in more than a thousand recognition problems
in three continuous domains and six classical planning domains.
},
}