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

We present a lazy incremental search algorithm, Lifelong-GLS (L-GLS), alongwith its bounded suboptimal version, Bounded L-GLS (B-LGLS) that combine thesearch efficiency of incremental search algorithms with the evaluationefficiency of lazy search algorithms for fast replanning in problem domainswhere edge-evaluations are more expensive than vertex-expansions. The proposedalgorithms generalize Lifelong Planning A* (LPA*) and its bounded suboptimalversion, Truncated LPA* (TLPA*), within the Generalized Lazy Search (GLS)framework, so as to restrict expensive edge evaluations only to the currentshortest subpath when the cost-to-come inconsistencies are propagated duringrepair. We also present dynamic versions of the L-GLS and B-LGLS algorithms,called Generalized D* (GD*) and Bounded Generalized D* (B-GD*), respectively,for efficient replanning with non-stationary queries, designed specifically fornavigation of mobile robots. We prove that the proposed algorithms are completeand correct in finding a solution that is guaranteed not to exceed the optimalsolution cost by a user-chosen factor. Our numerical and experimental resultssupport the claim that the proposed integration of the incremental and lazysearch frameworks can help find solutions faster compared to the regularincremental or regular lazy search algorithms when the underlying graphrepresentation changes often.

Lazy Incremental Search for Efficient Replanning with Bounded Suboptimality Guarantees