In this paper we study bidirectional state space search with consistent heuristics, with a
focus on obtaining sufficient conditions for node expansion, that is, conditions characterizing …

\emphReconfiguration problems require finding a step-by-step transformation between a
pair of feasible solutions for a particular problem. The primary concern in Theoretical …

We present a new algorithm called A*+ BFHS for solving problems with unit-cost operators
where A* and IDA* fail due to memory limitations and/or the existence of many distinct paths …

Best-first search algorithms such as A* need to apply tie-breaking strategies in order to
decide which node to expand when multiple search nodes have the same evaluation score …

In this line of work, we consider the possibility that some fast heuristic search methods
introduce structural bias, which can cause problems similar to sampling-bias for downstream …

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 …

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 …

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 …

Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple
agents from their start locations to end locations. We consider an extension to this problem …