Models of Search and Decision Making
Eugene Kagan, Irad Ben‐Gal · 2013
This chapter presents general models and methods for solving the search problems and considers the methods and algorithms which implement such methods. It describes the framework of Markov decision processes (MDPs) that supports a description of sequential decision making and provides unified solutions for a wide range of search problems. The chapter considers the methods of search and screening and of group-testing search; such a consideration is finalized by the White method of search. The formulation of the search problem in the form of MDP allows its direct consideration by use of the dynamic programming method, as initiated by Ross, and by the use of suitable learning methods. To illustrate this, the chapter also considers the Eagle and Washburn algorithms and their successors. The chapter includes particular models and algorithms of search which illustrate the MDP framework and generalize the previously considered methods, in particular the informational methods of search. Controlled Vocabulary Terms Markov decision process