Gal A. Kaminka's Publications

Sorted by DateClassified by Publication TypeClassified by TopicGrouped by Student (current)Grouped by Former Students

Comparing Plan Recognition Algorithms through Standard Libraries

Reuth Mirsky, Ran Galun, Yaakov (Kobi) Gal, and Gal A. Kaminka. Comparing Plan Recognition Algorithms through Standard Libraries. In AAAI workshop on Plan-, Activity-, and Intent- Recognition (PAIR), 2018.

Download

(unavailable)

Abstract

Plan recognition is one of the fundamental problems of AI, applicable to many domains, from user interfaces to cyber security. We focus on a class of algorithms that use plan libraries as input to the recognition process. Despite the prevalence of these approaches, they lack a standard representation, and have not been compared to each other on common testbeds. This paper directly addresses this gap by providing a standard plan library representation and evaluation criteria to consider. Our representation is comprehensive enough to describe a variety of known plan recognition problems, yet it can be easily applied to existing algorithms, which can be evaluated using our defined criteria. We demonstrate this technique on two known algorithms, SBR and PHATT. We provide meaningful insights both about the differences and abilities of the algorithms. We show that SBR is superior to PHATT both in terms of computation time and space, but at the expense of functionality and compact representation. We also show that depth is the single feature of a plan library that increases the complexity of the recognition, regardless of the algorithm used.

BibTeX

@inproceedings{pair18reuth,
	author = {Reuth Mirsky and Ran Galun and Yaakov (Kobi) Gal and Gal A. Kaminka},
	title = {Comparing Plan Recognition Algorithms through Standard Libraries},
	booktitle = {{AAAI} workshop on Plan-, Activity-, and Intent- Recognition ({PAIR})},
	year = {2018},
	abstract = {
	Plan recognition is one of the fundamental problems of AI, 
	applicable  to  many  domains,  from  user  interfaces  to  cyber 
	security. We focus on a class of algorithms that use plan libraries 
	as input to the recognition process. Despite the prevalence of 
	these approaches, they lack a standard representation, and 
	have not been compared to each other on common 
	testbeds. This paper directly addresses this gap by providing 
	a standard plan library representation and evaluation criteria 
	to consider. Our representation is comprehensive enough to 
	describe a variety of known plan recognition problems, yet 
	it can be easily applied to existing algorithms, which can be 
	evaluated using our defined criteria. 
	We  demonstrate  this  technique  on  two  known  algorithms, 
	SBR and PHATT. We provide meaningful insights both about 
	the differences and abilities of the algorithms. We show that 
	SBR is superior to PHATT both in terms of computation time 
	and space, but at the expense of functionality and compact representation. 
	We also show that depth is the single feature of a plan library that 
	increases the complexity of the recognition, regardless of the 
	algorithm used.
	},
}

Generated by bib2html.pl (written by Patrick Riley ) on Sat Feb 24, 2018 00:31:02