Algorithms for Decision Making

Abstract

Many important problems involve decision making under uncertainty, includingaircraft collision avoidance, wildfire management, and disaster response. Whendesigning automated decision-making systems or decision-support systems, it is important to account for various sources of uncertainty while carefully balancing multiple objectives. We will discuss these challenges from a computational perspective, aiming to provide the theory behind decision-making models and computational approaches. This chapter introduces the problem of decision making under uncertainty, provides some examples of applications, and outlines the space of computational approaches. It then summarizes how various disciplines have contributed to our understanding of intelligent decision making and highlights areas of potential societal impact. We conclude with an outline of the remainder of the book.