What question did this study set out to answer?

This research aims to develop an intelligent travel planning framework that adapts to real-time conditions.

May 5, 2026Open Access

AGENTIC AI TRIP PLANNER: Multi-Agent, Gemini-Powered Autonomous Framework for Intelligent, Real-Time Travel Planning and End-to-End Itinerary Optimization

Key Points

This research aims to develop an intelligent travel planning framework that adapts to real-time conditions.
Developed a multi-agent system powered by Gemini for travel planning.
Implemented algorithms for preference modeling and contextual reasoning.
Ensured adaptive itineraries through dynamic resource allocation based on real-time data.
Generated personalized itineraries that improved efficiency and reduced costs.
Responded effectively to real-time changes like flight delays and weather conditions.
Enhanced user satisfaction metrics through optimized travel experiences.

Abstract

The AGENTIC AI Trip Planner presents a multi‑agent, Gemini‑powered autonomous framework designed to transform travel planning into an intelligent, adaptive process. By orchestrating specialized agents for preference modeling, contextual reasoning, and dynamic resource allocation, the system generates personalized itineraries that respond to real‑time conditions such as flight delays, weather changes, and local events. This collaborative agent architecture ensures that itineraries are continuously optimized for efficiency, cost, and user satisfaction, moving beyond the limitations of static recommendation systems.

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