Bidirectional Bounded-Suboptimal Heuristic Search with Consistent Heuristics

TL;DR

This paper extends bidirectional heuristic search algorithms to the bounded-suboptimal setting, introducing variants of BAE* tailored for suboptimal solutions and evaluating their performance against existing algorithms.

Contribution

It presents novel variants of the BAE* algorithm for bounded-suboptimal bidirectional search, expanding the theoretical and practical understanding of suboptimal heuristic search methods.

Findings

Different algorithms excel under various conditions.

The new variants outperform some existing methods in specific scenarios.

Experimental results validate the effectiveness of the proposed algorithms.

Abstract

Recent advancements in bidirectional heuristic search have yielded significant theoretical insights and novel algorithms. While most previous work has concentrated on optimal search methods, this paper focuses on bounded-suboptimal bidirectional search, where a bound on the suboptimality of the solution cost is specified. We build upon the state-of-the-art optimal bidirectional search algorithm, BAE*, designed for consistent heuristics, and introduce several variants of BAE* specifically tailored for the bounded-suboptimal context. Through experimental evaluation, we compare the performance of these new variants against other bounded-suboptimal bidirectional algorithms as well as the standard weighted A* algorithm. Our results demonstrate that each algorithm excels under distinct conditions, highlighting the strengths and weaknesses of each approach.