508 citations · 562 across the 5 of their papers we have counts for
7 papers
Pseudo-Boolean Proof Logging for Optimal Classical Planning
Simon Dold, Malte Helmert, Jakob Nordström +2
We introduce lower-bound certificates for classical planning tasks, which can be used to prove the unsolvability of a task or the optimality of a plan in a way that can be verified…
A Formalism for Optimal Search with Dynamic Heuristics (Extended Version)
Remo Christen, Florian Pommerening, Clemens Büchner +1
While most heuristics studied in heuristic search depend only on the state, some accumulate information during search and thus also depend on the search history. Various existing a…
Higher-Dimensional Potential Heuristics for Optimal Classical Planning
Florian Pommerening, Malte Helmert, Blai Bonet
Potential heuristics for state-space search are defined as weighted sums over simple state features. Atomic features consider the value of a single state variable in a factored sta…
Iterative Budgeted Exponential Search
Malte Helmert, Tor Lattimore, Levi H. S. Lelis +2
We tackle two long-standing problems related to re-expansions in heuristic search algorithms. For graph search, A* can require expansions, where is the number of sta…
Exponential-Binary State-Space Search
Nathan Sturtevant, Malte Helmert
Iterative deepening search is used in applications where the best cost bound for state-space search is unknown. The iterative deepening process is used to avoid overshooting the ap…
Message-Based Web Service Composition, Integrity Constraints, and Planning under Uncertainty: A New Connection
Jörg Hoffmann, Piergiorgio Bertoli, Malte Helmert +1
Thanks to recent advances, AI Planning has become the underlying technique for several applications. Figuring prominently among these is automated Web Service Composition (WSC) at…
The Fast Downward Planning System
M. Helmert
Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, i…