A Behavior-first approach to Multi-Intention Inverse Reinforcement Learning
CoMI-IRL decouples behavior representation from reward learning in Multi-Intention Inverse Reinforcement Learning (MI-IRL). It uses a Transformer encoder to create trajectory embeddings, clusters these behaviors using a graph approach, and then learns a separate reward function for each cluster. This allows the system to understand different expert intentions without retraining when new behaviors appear.