User Tools
Sidebar
Damien Pellier
Laboratoire d'Informatique de Grenoble (UMR 5217)
Université Grenoble Alpes
Bâtiment IMAG – 700 avenue Centrale
Domaine Universitaire – 38401 St Martin d'Hères
damien.pellier@imag.fr
Office: 365
Phone: (+33) 4 57 42 15 39
Page web: http://lig-membres.imag.fr/pellier/
Background
I received a bachelor degree in telecomunication from the Annecy Institute of Technology, an engineering M.S degree in operating systems and network computing from the Polytech'Grenoble School and a M.S degree and a PhD. in Artificial Intelligence from the 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 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 Université Grenoble Alpes. My research is done in the laboratory of computer sciences of Grenoble (LIG) in the team Marvin.
Research Interest
My research is in Artificial Intelligence but specially robotics, 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.
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).
