This cluster of papers focuses on the modeling and optimization of dialogue acts in spoken language systems, utilizing techniques such as Markov decision processes, user simulation, multimodal interaction, reinforcement learning, natural language generation, and the hidden information state model. The research also delves into semantic processing, referring expressions, and the management of dialogues in various contexts.