This comparison should be conducted both in theory as well as empirically. In a very nutshell, this project is about comparing the pruning power of deadend detectors that are specific to the Sokoban game with the pruning power of general planning detectors, but with Sokoban being encoded as planning problem. Please take a look at any of my other projects should your marks not be strong enough. Since I plan to publish this work at an international top-tier (i.e., A*) conference, you should have very clear HD marks throughout.You don't need background on AI planning as learning that in the first two weeks should be easy.This project can be carried out as 12 pt project (but only over two semesters!) or as 24 pt Honours project.(I don't post this here so that I don't have to update all my project descriptions in case I don't accept more students.) Requirements Please check out the main page on research projects to see whether I'm maxed out. It might however be that I don't have capacities left in general. This project has been taken in 2022, so it will only be available again in S1 2024, since I'd like to have some break before I offer it again. Research Project: On Deadend Detection in Planning and Sokoban Project still available?

Online sokoban solver