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Dorit Avrahami-Zilberbrand and
Gal A. Kaminka. Towards Dynamic Tracking of Multi-Agents Teams: An Initial Report. In Proceedings of the AAAI
Workshop on Plan, Activity, and Intent Recognition (PAIR-07) , 2007.
This paper takes first steps to address the challenge of plan recognition for dynamicmulti-agents teams, in the context of suspicious behaviorrecognition. Plan recognition is the process of inferring otheragents' plans and goals based on their observable actions. Teamplan recognition poses the challenge of such inference, of a team's joint goals andplans. Most previous work have focused on recognizing specific(and limited) coordinated behaviors and do not deal with theproblem of identifying interactions between groups of agents, and withidentifying suspicious behavior from this information. In contrast, this paperutilizes the information from group of agents, to identify the interactions between groups of agents,using a Dynamic Hierarchical Group Model (DHGM) that tracks thedynamic grouping and ungrouping of agents. We show how such informationcan be used to identify potential suspiciousbehavior. These suspicious behaviors can be captured only when tracking individualswith respect to the group and not as individuals. For example,identifying passenger in the airport that behaves differently fromother passengers in the same group. While reasoning aboutindividual agents in a multi-agents framework is expensive, wereduce this complexity by utilizing the DHGM that encapsulateshared data of agents in the same group.
@InProceedings{pair07,
author = {Dorit Avrahami-Zilberbrand and Gal A. Kaminka},
title = {Towards Dynamic Tracking of Multi-Agents Teams: An Initial Report},
OPTcrossref = {},
OPTkey = {},
booktitle = {Proceedings of the {AAAI} Workshop on Plan, Activity, and Intent Recognition ({PAIR}-07) },
OPTpages = {},
year = {2007},
abstract = { This paper takes first steps to address the challenge of plan recognition for dynamic
multi-agents teams, in the context of suspicious behavior
recognition. Plan recognition is the process of inferring other
agents' plans and goals based on their observable actions. Team
plan recognition poses the challenge of such inference, of a team's joint goals and
plans. Most previous work have focused on recognizing specific
(and limited) coordinated behaviors and do not deal with the
problem of identifying interactions between groups of agents, and with
identifying suspicious behavior from this information. In contrast, this paper
utilizes the information from group of agents, to identify the interactions between groups of agents,
using a Dynamic Hierarchical Group Model (DHGM) that tracks the
dynamic grouping and ungrouping of agents. We show how such information
can be used to identify potential suspicious
behavior. These suspicious behaviors can be captured only when tracking individuals
with respect to the group and not as individuals. For example,
identifying passenger in the airport that behaves differently from
other passengers in the same group. While reasoning about
individual agents in a multi-agents framework is expensive, we
reduce this complexity by utilizing the DHGM that encapsulate
shared data of agents in the same group. },
wwwnote = {},
OPTeditor = {},
OPTvolume = {},
OPTnumber = {},
OPTseries = {},
OPTaddress = {},
OPTmonth = {},
OPTorganization = {},
OPTpublisher = {},
OPTnote = {},
OPTnote = {},
OPTannote = {}
}
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