We study the impact of tie-breaking on the behavior of greedy best-first search with a fixed
state space and fixed heuristic. We prove that it is NP-complete to determine the number of …

Balancing exploration and exploitation has been an important problem in both adversarial
games and automated planning. While it has been extensively analyzed in the Multi-Armed …

This paper introduces the Feature Space Search algorithm (FESS) that projects a single-
agent application search space onto an abstract space that is defined by features of the …

Satisficing heuristic search such as greedy best-first search (GBFS) suffers from local
minima, regions where heuristic values are inaccurate and a good node has a worse …

Heuristic forward search is currently the dominant paradigm in classical planning. Forward
search algorithms typically rely on a single, relatively simple variation of best-first search and …

Many problems of interest can be solved using heuristic search algorithms. When solving a
heuristic search problem, we are often interested in estimating search progress, that is, how …

Problem difficulty for greedy best first search (GBFS) is not entirely understood, though
existing work points to deep local minima and poor correlation between the h-values and the …

Stochastic exploration has been shown to be an effective way to mitigate the negative
impact that heuristic local minima and plateaus can have on Greedy Best First Search …

Although A* search can be efficiently parallelized using methods such as Hash-Distributed
A*(HDA*), distributed parallelization of Greedy Best First Search (GBFS), a suboptimal …

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 …