A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models

Understand

Recent studies have highlighted their proficiency in some simple tasks like writing and coding through various reasoning strategies.

• However, LLM agents still struggle with tasks that require comprehensive planning, a process that challenges current models and remains a critical research issue.
• In this study, we concentrate on travel planning, a Multi-Phases planning problem, that involves multiple interconnected stages, such as outlining, information gathering, and planning, often characterized by the need to manage various constraints and uncertainties.
• Existing reasoning approaches have struggled to effectively address this complex task.