We propose a purely logical framework for planning in partially observable environments. Knowledge states are expressed in a suitable fragment of the epistemic logic S5. We show h...
We propose an epistemic dynamic logic EDL able to represent the interactions between action and knowledge that are fundamental to planning under partial observability. EDL enables...
Partially observed actions are observations of action executions in which we are uncertain about the identity of objects, agents, or locations involved in the actions (e.g., we kn...
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...