In cost-optimal planning we aim to find a sequence of operators that achieve a set of goals
with minimum cost. Symbolic search with Binary Decision Diagrams (BDDs) performs …

Lately, several important advancements have been obtained in symbolic search. First,
bidirectional blind search has obtained good results on many domains. Second, perimeter …

Research on heuristic functions is all about estimating the length (or cost) of solution paths.
But what if there is no such path? Many known heuristics have the ability to detect (some) …

The International Planning Competition (IPC) is a prominent event of the artificial
intelligence planning community that has been organized since 1998; it aims at fostering the …

SymK is a planner that performs symbolic search using Binary Decision Diagrams to find a
single optimal or the best k plans. It is designed to be a versatile planner by supporting …

Symbolic bidirectional uniform-cost search is a prominent technique for cost-optimal
planning. Thus, the question whether it can be further improved by making use of heuristic …

Conflict-directed learning is ubiquitous in constraint satisfaction problems like SAT, but has
been elusive for state space search on reachability problems like classical planning. Almost …

The cost-optimal track of the international planning competition in 2014 has seen an
unexpected outcome. Different to the precursing competition in 2011, where explicit-state …

We introduce a state space search method that identifies dead-end states, analyzes the
reasons for failure, and learns to avoid similar mistakes in the future. Our work is placed in …

Heuristic search guides the exploration of states via heuristic functions h estimating
remaining cost. Symbolic search instead replaces the exploration of individual states with …