Advanced Algorithms for Search and Planning (AASP)
The course covers advanced algorithms for the following problem solving paradigms: state-space search, symbolic search, planning based on means-ends analysis (mostly approaches to partial order planning) and planning under uncertainty. The course assumes introductory knowledge of search and planning algorithms in AI (uninformed search, bestfirst search, and planning principles based on preconditions and effects of actions). The course includes advanced versions and extensions of search and planning algorithms, their theoretical properties, implementations and practical projects in combinatorial optimisation and robot programming. The course includes home assignments in experimentation with existing or own implementations of heuristic search on practical problems (with own ideas for heuristics), and a project in robot planning (or a planning problem of a student’s choice, possibly related to the topics of their PhD research).