Goal Recognition

Goal recognition (GR) aims to infer an agent's objectives from observed actions, a crucial problem in artificial intelligence with applications ranging from human-robot interaction to autonomous driving. Current research emphasizes developing more efficient and explainable GR models, employing techniques like Bayesian inference, reinforcement learning, linear programming, and data-driven approaches including deep learning architectures and process mining. These advancements improve GR accuracy, reduce computational costs, and enhance human understanding and trust in automated systems, ultimately fostering better human-agent collaboration and more robust AI systems.