
TUPLES is a three-year project focused on developing trustworthy AI solutions for Planning and Scheduling (P&S) systems. The project aims to create scalable, transparent, robust, and safe algorithmic approaches by combining symbolic P&S methods with data-driven techniques. This integration seeks to leverage the scalability of data-driven methods while retaining the transparency and robustness of symbolic reasoning. Key contributions include developing rigorous explanation and verification methods to ensure the trustworthiness of AI-driven decisions, particularly those involving machine learning. TUPLES will demonstrate and evaluate these novel methods across various real-world use cases, including manufacturing, aircraft operations, sports management, waste collection, and energy management. The project is funded by the European Union's HORIZON-CL4-2021-HUMAN-01 research and innovation program.

TUPLES is a three-year project focused on developing trustworthy AI solutions for Planning and Scheduling (P&S) systems. The project aims to create scalable, transparent, robust, and safe algorithmic approaches by combining symbolic P&S methods with data-driven techniques. This integration seeks to leverage the scalability of data-driven methods while retaining the transparency and robustness of symbolic reasoning. Key contributions include developing rigorous explanation and verification methods to ensure the trustworthiness of AI-driven decisions, particularly those involving machine learning. TUPLES will demonstrate and evaluate these novel methods across various real-world use cases, including manufacturing, aircraft operations, sports management, waste collection, and energy management. The project is funded by the European Union's HORIZON-CL4-2021-HUMAN-01 research and innovation program.