DESCARWIN - the hybridization of Descartes and Darwin - is based on Divide and Evolve, an original approach to Temporal Planning Problems (TPPs) solving (see the seminal paper here). The target TPP is decomposed into a sequence of (hopefully simpler) TPPs by means of artificial evolution, and each TPP of the series is handled by a standard solver.
- Domain knowledge gathered from the initial TPP should be used to improve all evolutionary operators, from initialization to crossover and mutation
- The parameters of the Evolutionary Algorithms need to be automatically adapted to the domain, or even to the instance. An important issue regards the identification of the characteristics of a domain that are common to all isntances - if any.
- Different planners can be used to solve the small TPPs, and should be compared within DAE. Ultimately, the evolutionary algorithm itself can be used to chose, for each sub-TPP, the most efficient planner.
- Using Evolutionary Algorithms opens the path to Multi-Objective optimization (e.g. the duration of a plan and its cost, or risk, or ...). Though the proof of concept has already been proposed in the seminal work, ot remains to be validated on large TPP. In particular, there is a need for a benchmark suite to be designed.
- The position is available immediately (January 2010)
- The post-doc will be located at LRI in the INRIA project-team TAO
Contact: Marc Schoenauer