A layered adjustable autonomy approach for dynamic autonomy distribution

Salama A. Mostafa, Mohd Sharifuddin Ahmad, Muthukkaruppan Annamalai, Azhana Ahmad, Ghusoon Salim Basheer

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

10 Citations (Scopus)

Abstract

Autonomy adjustment to a system requires a mechanism to implement the roles of the autonomous entities in the system. The required degree of autonomy to which the autonomous entities adhere is a highly debated topic. On one hand, people argue that strict minimal autonomy to the autonomous entities is sufficient in producing reliable systems. On the other hand, others deliberate that the entities with full autonomic capabilities are essential aspects of advanced intelligent and flexible systems. The adjustable autonomic agent approach can be a solution for both cases. In this paper, we extend the idea of modeling a spectrum of autonomy in a layered structure, where the agents can act at different layers of autonomy in order to fulfill the system's autonomic conditions. Consequently, a logical representation of the conceptual model of Layered Adjustable Autonomy (LAA) is proposed. The LAA model aims to give the system implicit control over the agents' decisions whenever necessary by managing the agents' autonomy, ensuring quality and robust decision-making. An Autonomy Analysis (AAM) and Situation Awareness (SAM) Modules are proposed to attest the dynamic distribution of agent autonomic performance to a degree of autonomy level.

Original languageEnglish
Title of host publicationAdvanced Methods and Technologies for Agent and Multi-Agent Systems
Pages335-345
Number of pages11
DOIs
Publication statusPublished - 01 Dec 2013

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume252
ISSN (Print)0922-6389

Fingerprint

Decision making
Control systems

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Mostafa, S. A., Ahmad, M. S., Annamalai, M., Ahmad, A., & Basheer, G. S. (2013). A layered adjustable autonomy approach for dynamic autonomy distribution. In Advanced Methods and Technologies for Agent and Multi-Agent Systems (pp. 335-345). (Frontiers in Artificial Intelligence and Applications; Vol. 252). https://doi.org/10.3233/978-1-61499-254-7-335
Mostafa, Salama A. ; Ahmad, Mohd Sharifuddin ; Annamalai, Muthukkaruppan ; Ahmad, Azhana ; Basheer, Ghusoon Salim. / A layered adjustable autonomy approach for dynamic autonomy distribution. Advanced Methods and Technologies for Agent and Multi-Agent Systems. 2013. pp. 335-345 (Frontiers in Artificial Intelligence and Applications).
@inproceedings{fb2880e5b56a4096b31cb838ed4c68b5,
title = "A layered adjustable autonomy approach for dynamic autonomy distribution",
abstract = "Autonomy adjustment to a system requires a mechanism to implement the roles of the autonomous entities in the system. The required degree of autonomy to which the autonomous entities adhere is a highly debated topic. On one hand, people argue that strict minimal autonomy to the autonomous entities is sufficient in producing reliable systems. On the other hand, others deliberate that the entities with full autonomic capabilities are essential aspects of advanced intelligent and flexible systems. The adjustable autonomic agent approach can be a solution for both cases. In this paper, we extend the idea of modeling a spectrum of autonomy in a layered structure, where the agents can act at different layers of autonomy in order to fulfill the system's autonomic conditions. Consequently, a logical representation of the conceptual model of Layered Adjustable Autonomy (LAA) is proposed. The LAA model aims to give the system implicit control over the agents' decisions whenever necessary by managing the agents' autonomy, ensuring quality and robust decision-making. An Autonomy Analysis (AAM) and Situation Awareness (SAM) Modules are proposed to attest the dynamic distribution of agent autonomic performance to a degree of autonomy level.",
author = "Mostafa, {Salama A.} and Ahmad, {Mohd Sharifuddin} and Muthukkaruppan Annamalai and Azhana Ahmad and Basheer, {Ghusoon Salim}",
year = "2013",
month = "12",
day = "1",
doi = "10.3233/978-1-61499-254-7-335",
language = "English",
isbn = "9781614992530",
series = "Frontiers in Artificial Intelligence and Applications",
pages = "335--345",
booktitle = "Advanced Methods and Technologies for Agent and Multi-Agent Systems",

}

Mostafa, SA, Ahmad, MS, Annamalai, M, Ahmad, A & Basheer, GS 2013, A layered adjustable autonomy approach for dynamic autonomy distribution. in Advanced Methods and Technologies for Agent and Multi-Agent Systems. Frontiers in Artificial Intelligence and Applications, vol. 252, pp. 335-345. https://doi.org/10.3233/978-1-61499-254-7-335

A layered adjustable autonomy approach for dynamic autonomy distribution. / Mostafa, Salama A.; Ahmad, Mohd Sharifuddin; Annamalai, Muthukkaruppan; Ahmad, Azhana; Basheer, Ghusoon Salim.

Advanced Methods and Technologies for Agent and Multi-Agent Systems. 2013. p. 335-345 (Frontiers in Artificial Intelligence and Applications; Vol. 252).

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

TY - GEN

T1 - A layered adjustable autonomy approach for dynamic autonomy distribution

AU - Mostafa, Salama A.

AU - Ahmad, Mohd Sharifuddin

AU - Annamalai, Muthukkaruppan

AU - Ahmad, Azhana

AU - Basheer, Ghusoon Salim

PY - 2013/12/1

Y1 - 2013/12/1

N2 - Autonomy adjustment to a system requires a mechanism to implement the roles of the autonomous entities in the system. The required degree of autonomy to which the autonomous entities adhere is a highly debated topic. On one hand, people argue that strict minimal autonomy to the autonomous entities is sufficient in producing reliable systems. On the other hand, others deliberate that the entities with full autonomic capabilities are essential aspects of advanced intelligent and flexible systems. The adjustable autonomic agent approach can be a solution for both cases. In this paper, we extend the idea of modeling a spectrum of autonomy in a layered structure, where the agents can act at different layers of autonomy in order to fulfill the system's autonomic conditions. Consequently, a logical representation of the conceptual model of Layered Adjustable Autonomy (LAA) is proposed. The LAA model aims to give the system implicit control over the agents' decisions whenever necessary by managing the agents' autonomy, ensuring quality and robust decision-making. An Autonomy Analysis (AAM) and Situation Awareness (SAM) Modules are proposed to attest the dynamic distribution of agent autonomic performance to a degree of autonomy level.

AB - Autonomy adjustment to a system requires a mechanism to implement the roles of the autonomous entities in the system. The required degree of autonomy to which the autonomous entities adhere is a highly debated topic. On one hand, people argue that strict minimal autonomy to the autonomous entities is sufficient in producing reliable systems. On the other hand, others deliberate that the entities with full autonomic capabilities are essential aspects of advanced intelligent and flexible systems. The adjustable autonomic agent approach can be a solution for both cases. In this paper, we extend the idea of modeling a spectrum of autonomy in a layered structure, where the agents can act at different layers of autonomy in order to fulfill the system's autonomic conditions. Consequently, a logical representation of the conceptual model of Layered Adjustable Autonomy (LAA) is proposed. The LAA model aims to give the system implicit control over the agents' decisions whenever necessary by managing the agents' autonomy, ensuring quality and robust decision-making. An Autonomy Analysis (AAM) and Situation Awareness (SAM) Modules are proposed to attest the dynamic distribution of agent autonomic performance to a degree of autonomy level.

UR - http://www.scopus.com/inward/record.url?scp=84894681535&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84894681535&partnerID=8YFLogxK

U2 - 10.3233/978-1-61499-254-7-335

DO - 10.3233/978-1-61499-254-7-335

M3 - Conference contribution

SN - 9781614992530

T3 - Frontiers in Artificial Intelligence and Applications

SP - 335

EP - 345

BT - Advanced Methods and Technologies for Agent and Multi-Agent Systems

ER -

Mostafa SA, Ahmad MS, Annamalai M, Ahmad A, Basheer GS. A layered adjustable autonomy approach for dynamic autonomy distribution. In Advanced Methods and Technologies for Agent and Multi-Agent Systems. 2013. p. 335-345. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-254-7-335