This repository presents an Artificial Intelligence (AI) case study focused on action planning for an automated warehouse. It is based on the STRIPS (Stanford Research Institute Problem Solver) model, a well-known planning approach in AI.
This project was developed as part of the Artificial Intelligence course, a discipline within the Bachelor’s Degree in Computer Engineering at Politecnico di Milano.
The project models an intelligent agent (robot) that interacts with an automated warehouse environment and plans its actions rationally to achieve a specific goal: delivering packages to designated exit zones.
Using formal action representation, this system applies fundamental principles of AI planning, including:
- Action preconditions and effects
- Sequential action planning
- Goal-oriented behavior
- Task automation and execution
For a detailed explanation of the theoretical background, refer to the full project report: Link to report.