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PhD Thesis in Automation/ Computer Science – CROSSING project

This offer is available in the following languages:
Français - Anglais

Date Limite Candidature : mercredi 6 juillet 2022

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General information

Reference : UMR8201-JOSBRO-011
Date of publication : Wednesday, June 15, 2022
Scientific Responsible name : Marie-Pierre PACAUX / Emmanuelle GRISLIN
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2022
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

Title : Cooperation between Human and AI-based system cooperation: assistance to organization and communication

As the maturity level of technology is increasing, we can now envision a real complementarity between humans and machines. The so-called “Human automation” highlighted the numerous possible combinations of complementary or shared tasks between human and machine. However, the levels of automation provided by this field focus on specific application domains and restrain combinations to rigid forms of cooperation. They do not take into account neither human capacity of adaptation, nor new abilities of technology based on artificial intelligence [1]. Human-Machine Cooperation approaches have instigated research studies addressing the definition of adaptive levels of automation. A methodology has been proposed with the objective to consider in the similar way human and artificial agents' competences (know-how, expertise, skills) and their capacity (workload, fatigue, energy consumption) to design and adapt cooperation according to situations) [2]. The adaptation concerns changes in agents' capacity and competence to control situations, but also changes in agents' capacity and competence to control cooperation (know-how-to-cooperate) [2]. The models proposed by the Human-Machine Cooperation field are now ready to be translated to models proposed by the Multi-Agent Systems field, and then implemented by the Artificial Intelligence field.
The objective of the PhD is to merge the advances of automation dealing with the integration of human decision making and control with the advances of artificial intelligence dealing with system ability to learn from human. The goal is, for human and machine, to learn from each other functions to control situations, but also to learn about each other to build up efficient cooperation. This topic aims at emphasizing the agents' abilities to communicate and to exploit knowledge reasoning in order to support building and updating a representation of the other agent. The machine must be able to explain its abilities, but also what it understands from/about human's abilities. The design of a Common Work Space can be the support of such a communication, by enabling and making easier information sharing about situation, but most importantly information sharing about agents [3]. Agents would be able to develop “Team Situation Awareness” and would be “transparent” to each other. Human may be more confident in machine, even if overconfidence and Human-out-of-the-loop risks must be carefully monitored and controlled. Studies dealing with ethic aspects start to provide interesting clues to reach this goal [4].
The application field is crisis management, and more precisely how humans and robots may share or trade functions to control crisis situations, like the control of a fire in an open environment. Works from a previous LAMIH project so-called “SUCRé” may be continued by implementing cooperation between human and artificial agents, involved at tactical decision levels (support for decision making) or at operational decisional levels (robots).
[1] M.-P. Pacaux-Lemoine, Human-Machine Cooperation: Adaptability of shared functions between Humans and Machines - Design and evaluation aspects. Valenciennes: Habilitation à Diriger des Recherches, Université Polytechnique Hauts-de-France, France, 2020.
[2] L. Habib, M. P. Pacaux-Lemoine, and P. Millot, “A method for designing levels of automation based on a human-machine cooperation model,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 1372–1377, 2017.
[3] P. Millot and M. P. Pacaux-Lemoine, “A common work space for a mutual enrichment of human-machine cooperation and team-situation awareness,” IFAC Proc. Vol., vol. 12, no. PART 1, pp. 387–394, 2013.
[4] M.-P. Pacaux-Lemoine and D. Trentesaux, “ETHICAL RISKS of HUMAN-MACHINE SYMBIOSIS in INDUSTRY 4.0: INSIGHTS from the HUMAN-MACHINE COOPERATION APPROACH,” in IFAC-PapersOnLine, 2019, vol. 52, no. 19.

Required skills:
The candidate should have experience in Computer Science, Automation or Robotics, and knowledge or experience in the human factors domain. The candidate must be able to communicate in English.

Work Context

The PhD study takes part in a collaboration in the international laboratory CROSSING: French-Australian Laboratory for Humans / Autonomous Agents Teaming
CROSSING addresses the Human-Autonomous agents cooperation topic with a multidisciplinary approach. The project results from 2 years of interaction of Cognitive Psychology, Artificial Intelligence and Robotics experts of the IRL. More precisely, the PhD subject takes part in the 4th section of the IRL roadmap about managing hybrid teams in which multidiscipline cooperation is required. The study implies a mirror duo in Crossing, with Anna Ma-Wyatt (Univ. of Adelaide, Cognitive Psychology) et Paulo Santos (Flinders, AI). Several stays in Adelaide will be planned.

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