Decision-Theoretic Planning

A computational approach to planning that uses mathematical models of decision-making under uncertainty, most commonly Markov Decision Processes (MDPs), to select optimal actions based on the current state of the system and predicted outcomes. In assistive technology, decision-theoretic planning enables systems to adapt their behaviour to individual users by learning from observed interactions — for example, choosing between different types of navigation directions based on which approach a particular user follows most successfully. This allows assistive systems to personalise their support without requiring explicit user configuration.