English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Partial MaxSAT (PMS) and Weighted PMS (WPMS) are two practicalgeneralizations of the MaxSAT problem. In this paper, we propose a local searchalgorithm for these problems, called BandHS, which applies two multi-armedbandits to guide the search directions when escaping local optima. One banditis combined with all the soft clauses to help the algorithm select to satisfyappropriate soft clauses, and the other bandit with all the literals in hardclauses to help the algorithm select appropriate literals to satisfy the hardclauses. These two bandits can improve the algorithm's search ability in bothfeasible and infeasible solution spaces. We further propose an initializationmethod for (W)PMS that prioritizes both unit and binary clauses when producingthe initial solutions. Extensive experiments demonstrate the excellentperformance and generalization capability of our proposed methods, that greatlyboost the state-of-the-art local search algorithm, SATLike3.0, and thestate-of-the-art SAT-based incomplete solver, NuWLS-c.

Incorporating Multi-armed Bandit with Local Search for MaxSAT