Abstract
Correlation Complexity of Classical Planning Domains / 3242 Jendrik Seipp, Florian Pommerening, Gabriele Röger, Malte Helmert
We analyze how complex a heuristic function must be to directly guide a state-space search algorithm towards the goal. As a case study, we examine functions that evaluate states with a weighted sum of state features. We measure the complexity of a domain by the complexity of the required features. We analyze conditions under which the search algorithm runs in polynomial time and show complexity results for several classical planning domains.
