Abstract
The adoption of unmanned systems is growing at a steady rate, with the promise of improved task effectiveness and decreased costs associated with an increasing multitude of operations. The added flexibility that could potentially enable a single operator to control multiple unmanned platforms is thus viewed as a potential game-changer in terms of both cost and effectiveness. The use of advanced technologies that facilitate the control of multiple systems must lie within control frameworks that allow the delegation of authority between the human and the machine(s). Agent-based systems have been used across different domains in order to offer support to human operators, either as a form of decision support offered to the human or to directly carry out behaviours that lead to the achievement of a defined goal. This paper discusses the need for adopting a human–agent interaction paradigm in order to facilitate an effective human–agent partnership. An example of this is discussed, in which a single human operator may supervise and control multiple unmanned platforms within an emergency response scenario.
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Notes
Pilot authorisation and control of tasks. See Bonner et al. (2000).
National highway traffic safety administration.
References
Baxter JW, Richards D (2010) Whose goal is it anyway? user interaction in an autonomous system. In: Proceedings of the workshop on goal directed autonomy, AAAI2010, Atlanta
Beer RD (1995) A dynamical systems perspective on agent–environment interaction. Artif Intell 72:173–215
Biehl M, Prater E, Realff MJ (2007) Assessing performance and uncertainty in developing carpet reverse logistics systems. Computers & Operations Research 34:443-463
Bolstad CA, Cuevas HM (2010) Integrating Situation Awareness Assessment into Test and Evaluation. ITEA J 31:240–246
Bonner MC, Taylor RM, Fletcher K, Miller C (2000) Adaptive automation and decision aiding in the military fast jet domain. In: CD proceedings of the conference on human performance, situation awareness and automation: user-centered design for the new millennium, Savannah, pp 154–159
Bratman M (1984) Two faces of intention. Philos Rev 93(3):375–405
Brooks RA (1991) Intelligence without representation. Artif Intell 47(13):139–159
Castelfranchi C (1995) Guarantees for autonomy in cognitive agent architecture. In: Wooldridge M, Jennings NR (eds) Intelligent agents: theories, architectures, and languages (LNAI volume 890). Springer, pp 56–70
Cetin O, Kurnaz S, Kaynak O (2011) Fuzzy logic based approach to design of autonomous landing system for unmanned aerial vehicles. J Intell Rob Syst 61(1):239–250
Chemero A (2009) Radical embodied cognitive science. MIT Press, Cambridge
Clark A (1997) Being there: putting brain, body and world together again. MIT Press, Cambridge
Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Human Factors 37(1):32–64
Endsley MR, Jones WM (1997) Situation awareness, information dominance, and information warfare (No.AL/CF-TR-1997-0156). Wright-Patterson AFB, OH, United States Air Force Armstrong Laboratory
Ernest N, Cohen K (2015) Fuzzy logic based intelligent agents for unmanned combat aerial vehicle control. J Def Manag 6:139. doi:10.4172/2167-0374.1000139
Gambetta D (ed) (1988) Trust: Making and breaking cooperative relations. Basil Blackwell Ltd, Oxford, UK
Gigliotta O, Nolfi S (2012) On the coupling between agent internal and agent/environmental dynamics: development of spatial representations in evolving autonomous robots. Adapt Behav 16:148–165
Gray SA, Zanre E, Gray SRJ (2014) Fuzzy cognitive maps as representations of mental models and group beliefs. In: Papageorgiou EI (ed) Fuzzy cognitive maps for applied sciences and engineering. Intelligent systems reference library, vol 54. Springer, Berlin, Heidelberg, pp 29–48
Grivault L, Fallah-Seghrouchni A, Girard-Claudon R (2016) Agent-based architecture for multi-sensors system deployed on airborne platform. In: IEEE international conference on agents (ICA), 28–30 Sept 2016
Grosz BJ, Sidner C (1990) Plans for discourse. In Cohen, Morgan and Pollack (eds) Intentions in communications, MIT Press, Chapter 20, pp 417–444
Hardin R (2002) Trust and trustworthiness. Russell Sage Foundation, New York
Heath BL, Hill RR (2010) Some insights into the emergence of agent-based modelling. J Simul 4(3):163–169
Jennings NR, Sycara K, Wooldridge M (1998) A roadmap of agent research and development. Auton Agent Multi-Agent Syst 1:7–38
Johnson-Laird PN (1983) Mental models: towards a cognitive science of language, inference, and consciousness. Cambridge University Press, Cambridge
Johnson-Laird PN, Byrne RMJ (1991) Deduction. Lawrence Erlbaum, Hillsdale
Levesque HJ, Cohen PR, Nunes JHT (1990) On acting together. In: 8th national conference on artificial intelligence, pp 94–99
Mayer RC, Davis JH, Schoorman FD (1995) An integrative model of organizational trust. Acad Manag Rev 20:709–734
McKnight DH, Chervany NL (2001) Trust and distrust definitions: one bite at a time. In: Falcone R, Singh M, Tan YH (eds) Trust in Cyber-Societies: integrating the human and artificial perspectives. Springer, Berlin, pp 27–54
Novak JD, Canas AJ (2008) The theory underlying concept maps and how to construct and use them. Technical report IHMC CmapTools 2006-01 Rev 01-2008. Institute for Human and Machine Cognition, p 36
Parush A, Ma C (2012) Team displays work, particularly with communication breakdown: Performance and situation awareness in a simulated forest fire. In the Proceedings of the Human Factors and Ergonomics Society, 56th Annual Meeting, pp 383–387
Pearson D, An E, Dhanak M, von Ellenreider K, Beaujean P (2014) High-level fuzzy logic guidance system for an unmanned surface vehicle (USV) tasked to perform autonomous launch and recovery (ALR) of an autonomous underwater vehicle (AUV). In: 2014 IEEE/OES autonomous underwater vehicles (AUV), pp 1–15, Oct 2014
Richards D (2017) Escape from the factory of the robot monsters: agents of change. Team Perform Manag Int J 23(1/2):96–108
Richards D, Stedmon A (2016) To delegate or not to delegate: a review of control frameworks for autonomous cars. Appl Ergon 53:383–388
Richards D, Stedmon A, Shaikh S, Davies D (2014) Responding to disaster using autonomous systems. The ergonomist (special feature), No. 534, Dec 2014
Simon H (1955) A behavioural model of rational choice. Q J Econ 69:99–118
Weimer CW, Miller JO, Hill RR (2016) Agent-based modelling: an introduction and primer. In: Proceedings of the 2016 winter simulation conference, INFORMS, Dec 11–14. Washington, DC
Wiedenbeck S (1999) The use of icons and labels in an end user application program: an empirical study of learning and retention. Behav Inf Technol 18(2):68–82
Wilson M (2002) Six views of embodied cognition. Psychon Bull Rev 9(4):625–636
Zeng Y, Jouandeau N, Cherif AA (2013) A survey and analysis of multi-robot coordination. Int J Adv Rob Syst 10:2013
Acknowledgements
This work was funded under the Growing Autonomous Mission Management Applications (GAMMA) programme. The author would like to express his thanks to the several reviewers who provided valuable suggestions on an earlier draft of this paper. Similarly, many thanks to Dr John Huddlestone, Guest Co-Editor of CTW, for his gentle reminders and advice.
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Richards, D., Stedmon, A. Designing for human–agent collectives: display considerations. Cogn Tech Work 19, 251–261 (2017). https://doi.org/10.1007/s10111-017-0419-1
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DOI: https://doi.org/10.1007/s10111-017-0419-1