MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue
MICA is a critic-free reinforcement learning framework for multi-turn emotional support dialogues. It solves sparse reward issues by deriving credit from both immediate and delayed effects using a shared potential function over the user's structured support state. This allows for stable, turn-by-turn optimization without needing complex matched states or learned critics.