A system architecture for decision-making support on isr missions with stochastic needs and profit

Nan Hu, Diego Pizzocaro, Thomas La Porta, Alun Preece

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a system architecture for decision-making support on ISR (i.e., Intelligence, Surveil- lance, Reconnaissance) missions via optimizing resource allocation. We model a mission as a graph of tasks, each of which often requires exclusive access to some resources. Our system guides users through refinement of their needs through an interactive interface. To maximize the chances of executing new missions, the system searches for pre-existent information collected on the field that best fit the needs. If this search fails, a set of new requests representing users' requirements is considered to maximize the overall benefit constrained by limited resources. zf an ISR request cannot be satisfied, feedback is generated to help the commander further refine or adjust their information requests in order to still provide support to the mission. In our work, we model both demands for resources and the importance of the information retrieved realistically in that they are not fully known at the time a mission is submitted and may change overtime during execution. The amount of resources consumed by a mission may not be deterministic; e.g., a mission may last slightly longer or shorter than expected, or more of a resource may be required to complete a task. Furthermore, the benefits received from the mission, which we call profits, may also be non-deterministic; e.g., successfully localizing a vehicle might be more important than expected for accomplishing the entire operation. Therefore, when satisfying ISR requirements we take into account both constraints on the underlying resources and uncertainty of demands and profits.

Original languageEnglish (US)
Title of host publicationGround/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV
DOIs
StatePublished - Sep 19 2013
EventGround/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV - Baltimore, MD, United States
Duration: Apr 29 2013May 2 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8742
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherGround/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV
CountryUnited States
CityBaltimore, MD
Period4/29/135/2/13

Fingerprint

decision making
System Architecture
Profit
Profitability
Decision making
Decision Making
resources
Resources
Resource allocation
reconnaissance
intelligence
surveillance
Feedback
Maximise
Requirements
user requirements
resource allocation
Resource Allocation
Refinement
Entire

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Hu, N., Pizzocaro, D., La Porta, T., & Preece, A. (2013). A system architecture for decision-making support on isr missions with stochastic needs and profit. In Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV [874203] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8742). https://doi.org/10.1117/12.2018047
Hu, Nan ; Pizzocaro, Diego ; La Porta, Thomas ; Preece, Alun. / A system architecture for decision-making support on isr missions with stochastic needs and profit. Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV. 2013. (Proceedings of SPIE - The International Society for Optical Engineering).
@inproceedings{a909b5a9eeab46c59af859928e469559,
title = "A system architecture for decision-making support on isr missions with stochastic needs and profit",
abstract = "In this paper, we propose a system architecture for decision-making support on ISR (i.e., Intelligence, Surveil- lance, Reconnaissance) missions via optimizing resource allocation. We model a mission as a graph of tasks, each of which often requires exclusive access to some resources. Our system guides users through refinement of their needs through an interactive interface. To maximize the chances of executing new missions, the system searches for pre-existent information collected on the field that best fit the needs. If this search fails, a set of new requests representing users' requirements is considered to maximize the overall benefit constrained by limited resources. zf an ISR request cannot be satisfied, feedback is generated to help the commander further refine or adjust their information requests in order to still provide support to the mission. In our work, we model both demands for resources and the importance of the information retrieved realistically in that they are not fully known at the time a mission is submitted and may change overtime during execution. The amount of resources consumed by a mission may not be deterministic; e.g., a mission may last slightly longer or shorter than expected, or more of a resource may be required to complete a task. Furthermore, the benefits received from the mission, which we call profits, may also be non-deterministic; e.g., successfully localizing a vehicle might be more important than expected for accomplishing the entire operation. Therefore, when satisfying ISR requirements we take into account both constraints on the underlying resources and uncertainty of demands and profits.",
author = "Nan Hu and Diego Pizzocaro and {La Porta}, Thomas and Alun Preece",
year = "2013",
month = "9",
day = "19",
doi = "10.1117/12.2018047",
language = "English (US)",
isbn = "9780819495334",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV",

}

Hu, N, Pizzocaro, D, La Porta, T & Preece, A 2013, A system architecture for decision-making support on isr missions with stochastic needs and profit. in Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV., 874203, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8742, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV, Baltimore, MD, United States, 4/29/13. https://doi.org/10.1117/12.2018047

A system architecture for decision-making support on isr missions with stochastic needs and profit. / Hu, Nan; Pizzocaro, Diego; La Porta, Thomas; Preece, Alun.

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV. 2013. 874203 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8742).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A system architecture for decision-making support on isr missions with stochastic needs and profit

AU - Hu, Nan

AU - Pizzocaro, Diego

AU - La Porta, Thomas

AU - Preece, Alun

PY - 2013/9/19

Y1 - 2013/9/19

N2 - In this paper, we propose a system architecture for decision-making support on ISR (i.e., Intelligence, Surveil- lance, Reconnaissance) missions via optimizing resource allocation. We model a mission as a graph of tasks, each of which often requires exclusive access to some resources. Our system guides users through refinement of their needs through an interactive interface. To maximize the chances of executing new missions, the system searches for pre-existent information collected on the field that best fit the needs. If this search fails, a set of new requests representing users' requirements is considered to maximize the overall benefit constrained by limited resources. zf an ISR request cannot be satisfied, feedback is generated to help the commander further refine or adjust their information requests in order to still provide support to the mission. In our work, we model both demands for resources and the importance of the information retrieved realistically in that they are not fully known at the time a mission is submitted and may change overtime during execution. The amount of resources consumed by a mission may not be deterministic; e.g., a mission may last slightly longer or shorter than expected, or more of a resource may be required to complete a task. Furthermore, the benefits received from the mission, which we call profits, may also be non-deterministic; e.g., successfully localizing a vehicle might be more important than expected for accomplishing the entire operation. Therefore, when satisfying ISR requirements we take into account both constraints on the underlying resources and uncertainty of demands and profits.

AB - In this paper, we propose a system architecture for decision-making support on ISR (i.e., Intelligence, Surveil- lance, Reconnaissance) missions via optimizing resource allocation. We model a mission as a graph of tasks, each of which often requires exclusive access to some resources. Our system guides users through refinement of their needs through an interactive interface. To maximize the chances of executing new missions, the system searches for pre-existent information collected on the field that best fit the needs. If this search fails, a set of new requests representing users' requirements is considered to maximize the overall benefit constrained by limited resources. zf an ISR request cannot be satisfied, feedback is generated to help the commander further refine or adjust their information requests in order to still provide support to the mission. In our work, we model both demands for resources and the importance of the information retrieved realistically in that they are not fully known at the time a mission is submitted and may change overtime during execution. The amount of resources consumed by a mission may not be deterministic; e.g., a mission may last slightly longer or shorter than expected, or more of a resource may be required to complete a task. Furthermore, the benefits received from the mission, which we call profits, may also be non-deterministic; e.g., successfully localizing a vehicle might be more important than expected for accomplishing the entire operation. Therefore, when satisfying ISR requirements we take into account both constraints on the underlying resources and uncertainty of demands and profits.

UR - http://www.scopus.com/inward/record.url?scp=84884149239&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84884149239&partnerID=8YFLogxK

U2 - 10.1117/12.2018047

DO - 10.1117/12.2018047

M3 - Conference contribution

AN - SCOPUS:84884149239

SN - 9780819495334

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV

ER -

Hu N, Pizzocaro D, La Porta T, Preece A. A system architecture for decision-making support on isr missions with stochastic needs and profit. In Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV. 2013. 874203. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2018047