Université Paris Descartes
Laboratoire d'Informatique de Paris Descartes IAD Team
45, rue des Saints Pères
F-75270 Paris cedex 06
damien.pellier@parisdescartes.fr
Bureau: 812-H
Phone: +33 1 83 94 57 86
Fax: +33 1 44 55 35 36

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 in Artificial Intelligence from the Grenoble I University. Since 2006, I am senior lecturer at the Paris Descartes University.

My research is in Artificial Intelligence but specially automated planning and scheduling, distributed planning, cooperative distributed problem solving and coordination, multiagent systems and recently in 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 observability, 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).