LAMA is a classical planning system based on heuristic forward search. Its core feature is
the use of a pseudo-heuristic derived from landmarks, propositional formulas that must be …

The performance of heuristic search-based planners depends heavily on the quality of the
heuristic function used to focus the search. These algorithms work fast and generate high …

LAMA is a propositional planning system based on heuristic search with landmarks. This
paper describes two versions of LAMA that were entered into the 2011 International …

Abstract Fast Downward Stone Soup is a sequential portfolio planner that uses various
heuristics and search algorithms that have been implemented in the Fast Downward …

Anytime variants of Dijkstra's and A* shortest path algorithms quickly produce a suboptimal
solution and then improve it over time. For example, ARA* introduces a weighting value" …

Anytime planning algorithms often have hyperparameters that can be tuned at runtime to
optimize their performance. While work on metareasoning has focused on when to interrupt …

Weighted A* is the most popular satisficing algorithm for heuristic search. Although there is
no formal guarantee that increasing the weight on the heuristic cost-to-go estimate will …

In this work, we present the FD-Autotune learning planning system, which is based on the
idea of domain-specific configuration of the latest, highly parametric version of the Fast …

Multi-modal journey planning, which allows multiple types of transport within a single trip, is
becoming increasingly popular, due to a strong practical interest and an increasing …

LAMA-2011 (Richter and Westphal 2010) is the clear winner of the sequential satisficing
track in the latest International Planning Competition (IPC-2011). It finds a first solution by …