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Active Goal Recognition Design.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Active Goal Recognition Design./
Author:	Gall, Kevin C.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	84 p.
Notes:	Source: Masters Abstracts International, Volume: 83-02.
Contained By:	Masters Abstracts International83-02.
Subject:	Artificial intelligence. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28493515
ISBN:	9798516963971

Active Goal Recognition Design.
Gall, Kevin C.

Active Goal Recognition Design. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 84 p.

Source: Masters Abstracts International, Volume: 83-02.

Thesis (M.S.)--University of New Hampshire, 2021.

This item must not be sold to any third party vendors.

In Goal Recognition Design (GRD), the objective is to modify a domain to facilitate early detection of the goal of a subject agent. Most previous work studies this problem in the offline setting, in which the observing agent performs its interventions before the subject begins acting. In this thesis, we generalize GRD to the online setting in which time passes and the observer's actions are interleaved with those of the subject. We illustrate weaknesses of existing metrics for GRD and propose an alternative better suited to online settings. We provide a formal definition of this Active GRD (AGRD) problem and propose both an optimal algorithm and a suboptimal algorithm for solving it. AGRD occupies an interesting middle ground between passive goal recognition and strategic two-player game settings.

ISBN: 9798516963971Subjects--Topical Terms:

516317
Artificial intelligence.
Subjects--Index Terms:

Game theory

Active Goal Recognition Design.
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300 $a 84 p.
500 $a Source: Masters Abstracts International, Volume: 83-02.
500 $a Advisor: Ruml, Wheeler.
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520 $a In Goal Recognition Design (GRD), the objective is to modify a domain to facilitate early detection of the goal of a subject agent. Most previous work studies this problem in the offline setting, in which the observing agent performs its interventions before the subject begins acting. In this thesis, we generalize GRD to the online setting in which time passes and the observer's actions are interleaved with those of the subject. We illustrate weaknesses of existing metrics for GRD and propose an alternative better suited to online settings. We provide a formal definition of this Active GRD (AGRD) problem and propose both an optimal algorithm and a suboptimal algorithm for solving it. AGRD occupies an interesting middle ground between passive goal recognition and strategic two-player game settings.
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