In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...
Heuristic functions make MDP solvers practical by reducing their time and memory requirements. Some of the most effective heuristics (e.g., the FF heuristic function) first determ...
Consider the task of a mobile robot autonomously navigating through an environment while detecting and mapping objects of interest using a noisy object detector. The robot must re...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
Earthwork projects involve moving specific amounts of earth from a discrete set of source locations to a discrete set of destinations. Constructors use different methods and equip...