Agent Q is the next-generation AI agent model developed by MultiOn. By integrating search, self-criticism, and reinforcement learning, it creates advanced autonomous web agents capable of planning and self-repair. It addresses the challenges of traditional large language models (LLMs) in multi-step reasoning tasks within dynamic environments, enhancing success rates in complex scenarios using guided Monte Carlo Tree Search (MCTS), AI self-criticism, and Direct Preference Optimization (DPO) algorithms.