A classical result in optimal search shows that A* with an admissible and consistent heuristic
expands every state whose f-value is below the optimal solution cost and no state whose f …

Depressions in raster digital elevation models (DEM) present a challenge for extracting
hydrological networks. They are commonly filled before subsequent algorithms are further …

Recent enhancements to greedy best-first search (GBFS) such as DBFS,-GBFS, Type-GBFS
improve performance by occasionally introducing exploratory behavior which occasionally …

A* is a classic and popular method for graphs search and path finding. It assumes the
existence of a heuristic function $ h (u, t) $ that estimates the shortest distance from any input …

In this paper we study the One-to-Many Shortest Path Problem (OMSPP), which is the
problem of solving k shortest path problems that share the same start node. This problem …

Referred to as an approach for either plan or goal recognition, the original method proposed
by Ramırez and Geffner introduced a domain-based approach that did not need a library …

For a given state space and admissible heuristic function h there is always a tie-breaking
strategy for which A* expands the minimum number of states (Dechter and Pearl 1985). We …

One key decision for heuristic search algorithms is how to balance exploration and
exploitation. In classical planning, novelty search has come out as the most successful …

Recent work has experimentally shown that parallelization of Greedy Best-First Search
(GBFS), a satisficing best-first search method, can behave very differently from sequential …

Diverse action costs are an essential feature of many real-world planning applications.
Some recent studies have shown that diversity of action costs makes planning more difficult …