# Nested Search versus Limited Discrepancy Search

arXiv: https://arxiv.org/abs/2210.00216 · HTML: https://mlsanity.com/paper/2210.00216/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 44 references that are in the map.
- First posted on arXiv 1 Oct 2022.

## Builds on (most cited first, 3 of 3)

- [Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization](https://mlsanity.com/paper/2006.01610/) (2020)
- [Monte Carlo Inverse Folding](https://mlsanity.com/paper/2005.09961/) (2020)
- [Effective problem solving using SAT solvers](https://mlsanity.com/paper/1906.06251/) (2019)

## Abstract (arXiv)

Limited Discrepancy Search (LDS) is a popular algorithm to search a state space with a heuristic to order the possible actions. Nested Search (NS) is another algorithm to search a state space with the same heuristic. NS spends more time on the move associated to the best heuristic playout while LDS spends more time on the best heuristic move. They both use similar times for the same level of search. We advocate in this paper that it is often better to follow the best heuristic playout as in NS than to follow the heuristic as in LDS.