FRAMING THE CONCEPT OF AUTONOMY IN SYSTEM DESIGN

Advancements in multiple domains have led to a focus on autonomy in engineered systems. This focus necessitates a clear definition of the term ‘autonomy’ and its implications for system design. To this end, we present a framework that defines autonomy mathematically as a function of independence and task complexity. A deeper understanding is established by generating design principles that can be used to influence autonomy. We illustrate these concepts on autonomy quantification for a coffee machine and on a qualitative retrospective assessment of the evolution of autonomy for the automobile.

[1]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[2]  Michael Wooldridge,et al.  Intelligent agents: theory and practice The Knowledge Engineering Review , 1995 .

[3]  Klaus Fischer,et al.  A Taxonomy of Autonomy in Multiagent Organisation , 2003, Agents and Computational Autonomy.

[4]  Jeffrey M. Bradshaw,et al.  Dimensions of Adjustable Autonomy and Mixed-Initiative Interaction , 2003, Agents and Computational Autonomy.

[5]  K. Suzanne Barber,et al.  Dynamic adaptive autonomy in multi-agent systems , 2000, J. Exp. Theor. Artif. Intell..

[6]  Bruce T Clough,et al.  Metrics, Schmetrics! How The Heck Do You Determine A UAV's Autonomy Anyway , 2002 .

[7]  Hui-Min Huang,et al.  Characterizing unmanned system autonomy: contextual autonomous capability and level of autonomy analyses , 2007, SPIE Defense + Commercial Sensing.

[8]  Panos J. Antsaklis,et al.  Towards intelligent autonomous control systems: Architecture and fundamental issues , 1989, J. Intell. Robotic Syst..

[9]  Robin R. Murphy,et al.  Introduction to AI Robotics , 2000 .

[10]  Aleksander Lodwich.  Differences between Industrial Models of Autonomy and Systemic Models of Autonomy , 2016, ArXiv.

[11]  Jenay M. Beer,et al.  Toward a framework for levels of robot autonomy in human-robot interaction , 2014, Journal of human-robot interaction.

[12]  Nils Masuch,et al.  A Metrics Framework for Quantifying Autonomy in Complex Systems , 2015, MATES.

[13]  D. Broadbent.  Perception and communication , 1958 .

[14]  Brian T. Pentland,et al.  Task Complexity: Extending a Core Concept , 2014 .

[15]  B. P. Zeigler,et al.  High autonomy systems: concepts and models , 1990, Proceedings [1990]. AI, Simulation and Planning in High Autonomy Systems.

[16]  Sebastian Thrun,et al.  Toward a Framework for Human-Robot Interaction , 2004, Hum. Comput. Interact..

[17]  Thomas B. Sheridan,et al.  Human and Computer Control of Undersea Teleoperators , 1978 .

[18]  Kristinn R. Thórisson,et al.  Cognitive Architectures and Autonomy: A Comparative Review , 2012, J. Artif. Gen. Intell..

[19]  Holly A. Yanco,et al.  Classifying human-robot interaction: an updated taxonomy , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[20]  D. Campbell.  Task Complexity: A Review and Analysis , 1988 .

[21]  George A. Bekey,et al.  AUTONOMOUS ROBOTS, From Biological Inspiration to Implementation and Control, by G.A. Bekey, MIT Press, 2005, xv + 577 pp., index, ISBN 0-262-02578-7, 25 pages of references (Hb. £35.95) , 2005, Robotica.

[22]  C. Castelfranchi,et al.  From Automaticity to Autonomy: The Frontier of Artificial Agents , 2003 .

[23]  M R Endsley,et al.  Level of automation effects on performance, situation awareness and workload in a dynamic control task. , 1999, Ergonomics.