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A Hybrid Pattern Based Design to Imp...

Phillips, Brian J.

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A Hybrid Pattern Based Design to Improve Real-Time System Adaptation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Hybrid Pattern Based Design to Improve Real-Time System Adaptation./
Author:	Phillips, Brian J.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	201 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
Subject:	Systems science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10275777
ISBN:	9780355096453

A Hybrid Pattern Based Design to Improve Real-Time System Adaptation.
Phillips, Brian J.

A Hybrid Pattern Based Design to Improve Real-Time System Adaptation. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 201 p.

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--Stevens Institute of Technology, 2017.

This dissertation investigates hybrid design strategies to improve performance of adaptive systems that must alter their own structure in real-time based upon changing operational conditions. The strategies focus on reducing the time to choose an adaptation based on information collected about the operational environment and its own internal states along with other inhabitants of that environment. This novel approach combines behavior selection algorithms (e.g. classifiers) with different temporal domains and embeds them into a two-system ensemble whose goal is to improve adaptation speed. This hybrid approach provides a method where adaptive systems collect information from their environment and their own internal states and use this information to choose behaviors that satisfy one or more end goals.

ISBN: 9780355096453Subjects--Topical Terms:

3168411
Systems science.

A Hybrid Pattern Based Design to Improve Real-Time System Adaptation.
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245 1 2 $a A Hybrid Pattern Based Design to Improve Real-Time System Adaptation.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 201 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Adviser: Mark Blackburn.
502 $a Thesis (Ph.D.)--Stevens Institute of Technology, 2017.
520 $a This dissertation investigates hybrid design strategies to improve performance of adaptive systems that must alter their own structure in real-time based upon changing operational conditions. The strategies focus on reducing the time to choose an adaptation based on information collected about the operational environment and its own internal states along with other inhabitants of that environment. This novel approach combines behavior selection algorithms (e.g. classifiers) with different temporal domains and embeds them into a two-system ensemble whose goal is to improve adaptation speed. This hybrid approach provides a method where adaptive systems collect information from their environment and their own internal states and use this information to choose behaviors that satisfy one or more end goals.
520 $a This research uses design techniques to improve the performance of real time systems with time constraints. It uses a metric of system survivability as a key performance parameter. A pattern-based design technique offers a novel method of addressing this problem. This research embraces a wide variety of behavior selection algorithms, embedding them into the two-system ensemble to improve adaptation speed.
520 $a This research focuses on design strategies that seek to overcome problems associated with time limitations. It incorporates classification techniques into the research approach. It assumes that no classification technique is sufficient to speed up adaptation decisions while ensuring that those decisions remain significant, and contribute to overall system performance (i.e. survivability).
520 $a To verify design strategies, this research effort uses a simulation environment composed of agents that combat each other within a virtual two-dimensional battlefield. Combat scenarios yield insights into the adaptation speed problem because it focuses on time-limited battles between simulated tanks with and without adaptive behaviors. It presents system survivability problems based upon these simulated tanks, and allows them to adapt and avoid failures while competing directly in combat, or for collecting limited resources.
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650 4 $a Systems science. $3 3168411
650 4 $a Artificial intelligence. $3 516317
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710 2 $a Stevens Institute of Technology. $b Systems Engineering. $3 3186847
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10275777