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 ~~NOTOC~~
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 ====== Humbert Fiorino ======
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 ** Phone: ** (+33) 4 57 42 14 95
+===== Publications =====
+[[members:fiorino:recent_works|Recent works]]\\
+[[members:fiorino:allpublications|Complete list]]
 ===== Background =====
 ###
-I received a bachelor degree in telecomunication from the [[http://www.iut-acy.univ-savoie.fr/|Annecy Institute of Technology]], an engineering M.S degree in operating systems and network computing from the [[http://www.polytech-grenoble.fr/|Polytech'Grenoble School]] and a M.S degree and a PhD. in Artificial Intelligence from the [[http://www.ujf-grenoble.fr/|Grenoble 1 University]] (Joseph Fourier University). I also hold a "Habilitation à diriger des recherches" form Grenoble Alpes University. Between 2006 and 2013, I was associate professor at [[http://www.parisdescartes.fr|Paris Descartes University]]. Between 2011 and 2013, I was vice-president of the bord director of Paris Descartes. Since 2013, I am associate professor at [[https://www.univ-grenoble-alpes.fr|Université Grenoble Alpes]]. My research is  done in the [[http://www.liglab.fr/|laboratory of computer sciences of Grenoble]] (LIG) in the [[http://marvin.imag.fr|team Marvin]].
+I received my Ph.D. degree from SUPAERO (Ecole nationale supérieure de l'aéronautique et de l'espace) and the ONERA (Office National d'Etudes et Recherches Aérospatiales). I visited the Robotics and Artificial Intelligence group at the LAAS (Laboratoire d'Analyse et d'Architecture des Systèmes) as postdoctoral fellow. This research work was supported by the DGA (Délégation Générale à l'Armement) and focused on AUV (Autonomous Underwater Vehicles) cooperation. Currently, I am Associate Professor in computer science at Grenoble Alpes University (UGA) and permanent researcher at Grenoble Informatics Laboratory (LIG).
 ###
  ===== Research Interest =====
+###
+I am interested in devising autonomous agents (softbots, physical robots etc.) Agent technologies envision artificial systems with a high degree of autonomy requiring only high-level supervision of human users. This autonomy simplifies human control and drastically improves the scope of agent achievable tasks. Fully autonomous agents are still out of reach: currently their performances under human remote control are very limited. However, in the near future, autonomous agents will become believable companions in our everyday lives and useful surrogates in dangerous or troublesome situations. The concepts and the algorithms that I investigate in my research works aim at contributing to the development of "autonomy technologies". This research effort is important to support the incipient industry of autonomous systems.
 ###
-My research is in ** Artificial Intelligence** but specially **automated planning and scheduling**, **distributed planning**, **cooperative distributed problem solving** and **coordination**, **multiagent systems** and ** machine learning**.
-Automated planning is a branch of artificial intelligence that concerns the realisation of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
-A typical planner takes three inputs: a description of the initial state of the world, a description of the desired goal, and a set of possible actions, all encoded in a formal language such as STRIPS. The planner produces a sequence of actions that lead from the initial state to a state meeting the goal. The difficulty of planning is dependent on the simplifying assumptions employed, e.g. atomic time, deterministic time, complete observabi
+###
-lity, etc. Classical planners make all these assumptions and have been studied most fully.
+**Keywords:** automated planning, machine learning, distributed planning, multiagent system, autonomous systems, cobotics, social robotics, Artificial Intelligence.
-Distributed planning is concerned with planning by (and for) multiple agents. It can involve agents planning for a common goal, an agent coordinating the plans (plan merging) or planning of others, or agents refining their own plans while negotiating over tasks or resources. The topic also involves how agents can do this in real time while executing plans (distributed continual planning).
 ###