Towards Online Goal Recognition Combining Goal Mirroring and Landmarks

Online goal recognition is the problem of recognizing the goal of an agent based on an incomplete sequence of incrementally revealed observations as early along the recognition process as possible. Recognizing goals with minimal domain knowledge as an agent executes its plan requires efficient algorithms to sift through a large space of hypotheses. We develop an online approach to goal recognition which operates in both continuous and discrete domains using a combination of Goal Mirroring and a generalized notion of landmarks adapted from the planning literature. Extensive experiments demonstrate the approach is more efficient and substantially more accurate than the state-of-the-art.