# Decoupling Generation and Evaluation for Parallel Greedy Best-First Search(extended version)

arXiv: https://arxiv.org/abs/2408.05682 · HTML: https://mlsanity.com/paper/2408.05682/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 10 references that are in the map.
- First posted on arXiv 11 Aug 2024.

## Builds on (most cited first, 1 of 1)

- [ePA*SE: Edge-based Parallel A* for Slow Evaluations](https://mlsanity.com/paper/2203.01369/) (2022)

## Abstract (arXiv)

In order to understand and control the search behavior of parallel search, recent work has proposed a class of constrained parallel greedy best-first search algorithms which only expands states that satisfy some constraint.However, enforcing such constraints can be costly, as threads must be waiting idly until a state that satisfies the expansion constraint is available. We propose an improvement to constrained parallel search which decouples state generation and state evaluation and significantly improves state evaluation rate, resulting in better search performance.