Book ChapterDOI
Agents and Decision Support Systems
Andreas Tolk,Poornima Madhavan,Jeffrey Tweedale,Lakhmi C. Jain +3 more
- pp 399-431
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This article is published in Agent-Directed Simulation.The article was published on 2010-02-12. It has received 3 citations till now. The article focuses on the topics: Decision support system & Intelligent decision support system.read more
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Book ChapterDOI
Modeling and Simulation as a Theory Building Paradigm
TL;DR: This chapter makes the case that theory can be captured as a model, which can be implemented as a simulation, which allows composing and recomposing theory components to process new theory out of existing theory using modeling and simulation.
OtherDOI
Life Learning of Smart Autonomous Systems for Meaningful Human-Autonomy Teaming
Abstract: As the world embraces the evolution of cognitive cyber–physical systems, there is an emergence of systems with the ability to comprehend and act on information efficiently while also supporting human operators to achieve ethically aligned mission objectives consistently. This human‐autonomy teaming (HAT) relationship will evolve with technology and increasing levels of autonomy. It is essential to identify the role of trust and systematically develop to that role to minimize challenges in HAT relationships. Life‐learning processes are needed to guide system developers to assess meaningful interactions and to refine the critical contexts that require trust continuously. By assessing the presence of trust, cognitive competence, and meaningful interactions, human factors specialists and human systems engineers will also be able to assess the sociotechnical system evolution. This chapter first defines trust, both as a concept and for use in HAT. It then proposes processes for how to assess trust, especially to meet recently proposed IEEE standards and United Nations articles concerning meaningful human control. The chapter then examines how our research program on the herding of sheep using unmanned aerial vehicles (UAVs) is validating HAT concepts and the proposed processes. The program is concerned with teaming farmers with smart autonomous capabilities to assure meaningful farmers' control. Meaningfulness needs to account for public obligations and ethical responsibilities. This application area potentially solves extant ethical challenges in shepherding in Australia concerning the use of dogs and timely monitoring and action in vast sheep stations while also allowing the investigation of ethical challenges around continually evolving artificial intelligence in the system. Ethically designed HAT systems are about pragmatic trade‐offs with prior processes, yet in this future context of life learning of intelligent systems, can now be revised through‐life with changing expectations and improvements.