Real-world decision-making problems rarely involve optimizing a single objective. Instead, autonomous systems must navigate trade-offs between multiple competing objectives such as efficiency, safety, robustness, fairness, or resource usage. As these systems are increasingly deployed in complex environments, the ability to reason about and learn these trade-offs has become an essential capability.

The Multi-Objective Decision Making Workshop (MODeM) workshop brings together researchers working on different aspects of multi-objective decision making, including reinforcement learning, evolutionary optimization, planning, and multi-agent systems. The goal is to foster collaboration and cross-fertilization of ideas across communities, and to provide a forum for presenting and discussing new theoretical insights, algorithms, and applications in multi-objective decision making.

In 2026, MODeM will be held at the joint IJCAI–ECAI conference. More details coming soon. Previous editions can be found here.