REBA: A Revealed Belief Automaton Framework for Online Planning in Continuous POMDPs (opens in new tab)

Online planning in continuous partially observable Markov decision processes (POMDPs) using $\omega$-regular specifications requires handling continuous belief dynamics within the finite symbolic memory in order to track temporal progress. Existing methods based on either direct search in belief space or predefined discrete abstractions suffer from drawbacks, e.g., lack of symbolic memory for long-horizon logical progress or difficult to certify...