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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Large language models (LLMs) have demonstrated remarkable zero-shotgeneralization abilities: state-of-the-art chatbots can provide plausibleanswers to many common questions that arise in daily life. However, so far,LLMs cannot reliably solve long-horizon planning problems. By contrast,classical planners, once a problem is given in a formatted way, can useefficient search algorithms to quickly identify correct, or even optimal,plans. In an effort to get the best of both worlds, this paper introducesLLM+P, the first framework that incorporates the strengths of classicalplanners into LLMs. LLM+P takes in a natural language description of a planningproblem, then returns a correct (or optimal) plan for solving that problem innatural language. LLM+P does so by first converting the language descriptioninto a file written in the planning domain definition language (PDDL), thenleveraging classical planners to quickly find a solution, and then translatingthe found solution back into natural language. Along with LLM+P, we define adiverse set of different benchmark problems taken from common planningscenarios. Via a comprehensive set of experiments on these benchmark problems,we find that LLM+P is able to provide optimal solutions for most problems,while LLMs fail to provide even feasible plans for most problems.\footnote{Thecode and results are publicly available athttps://github.com/Cranial-XIX/llm-pddl.git.

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency