Mixed-Initiative Human-Automated Agents Teaming: Towards a Flexible Cooperation Framework
| Autor: | Caroline Ponzoni Carvalho Chanel, Raphaëlle N. Roy, Nicolas Drougard, Frédéric Dehais |
|---|---|
| Přispěvatelé: | Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE), Artificial and Natural Intelligence Toulouse Institute - ANITI (FRANCE), Département Conception et conduite des véhicules Aéronautiques et Spatiaux (DCAS), Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science Aviation Sequential decision making under uncertainty and partial observability Control (management) Context (language use) 02 engineering and technology Human operator monitoring 020901 industrial engineering & automation Shared-autonomy 0501 psychology and cognitive sciences 050107 human factors business.industry [SCCO.NEUR]Cognitive science/Neuroscience 05 social sciences Neurosciences Partially observable Markov decision process Robotics POMDP 16. Peace & justice Variety (cybernetics) Identification (information) Action (philosophy) Risk analysis (engineering) Mixed-initiative interaction Artificial intelligence business |
| Zdroj: | Engineering Psychology and Cognitive Ergonomics. Cognition and Design ISBN: 9783030491826 HCI (7) Engineering Psychology and Cognitive Ergonomics. Cognition and Design. HCII 2020 22nd International Conference on Human-Computer Interaction-HCI INTERNATIONAL 2020 22nd International Conference on Human-Computer Interaction-HCI INTERNATIONAL 2020, Jul 2020, Copenhagen, Denmark. pp.117-133, ⟨10.1007/978-3-030-49183-3_10⟩ |
| DOI: | 10.1007/978-3-030-49183-3_10⟩ |
| Popis: | International audience; The recent progress in robotics and artificial intelligence raises the question of the efficient artificial agents interaction with humans. For instance, artificial intelligence has achieved technical advances in perception and decision making in several domains ranging from games to a variety of operational situations, (e.g. face recognition [51] and firefighting missions [23]). Such advanced automated systems still depend on human operators as far as complex tactical, legal or ethical decisions are concerned. Usually the human is considered as an ideal agent, that is able to take control in case of automated (artificial) agent's limit range of action or even failure (e.g embedded sensor failures or low confidence in identification tasks). However, this approach needs to be revised as revealed by several critical industrial events (e.g. aviation and nuclear power-plant) that were due to conflicts between humans and complex automated system [13]. In this context, this paper reviews some of our previous works related to human-automated agents interaction driving systems. More specifically, a mixed-initiative cooperation framework that considers agents' non-deterministic actions effects and inaccuracies about the human operator state estimation. This framework has demonstrated convincing results being a promising venue for enhancing human-automated agent(s) teaming. |
| Databáze: | OpenAIRE |
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