Heuristic search is a leading approach to domain-independent planning. For cost-optimal planning, however, existing admissible heuristics are generally too weak to effectively gui...
Patrik Haslum, Adi Botea, Malte Helmert, Blai Bone...
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
We show that global caching can be used with propagation of both satisfiability and unsatisfiability in a sound manner to give an EXPTIME algorithm for checking satisfiability w...
In recent work we showed that models constructed from planner performance data over a large suite of benchmark problems are surprisingly accurate; 91-99% accuracy for success and ...
Mark Roberts, Adele E. Howe, Brandon Wilson, Marie...