Generation of Tourist Routes Considering Preferences and Public Transport Using Artificial Intelligence Planning Techniques

This work aims to generate a planning model using knowledge representation techniques from artificial intelligence to plan the transfer routes and the sequence of visits to multiple points of interest for a tourist, addressing this as a Tourist Trip Design Problem. Our model considers user preferences as variables to be optimized or as constraints, which may include time, walking distances, and economic costs. To facilitate movement between different points of interest, we propose to use the public transportation network. The user specifies his starting point, his destination, and the points of interest he wants to visit, allowing for multi-day planning. The methodology used is an artificial intelligence planning model where actions, preferences, and spatial topology are modeled. Planning algorithms (planners) are used to solve the tourist trip design problem. A comparison of the results obtained by different planners is performed, demonstrating the effectiveness of using Artificial Intelligence Planning to solve such complex problems.