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A study of human control in a stochastic multistage decision task
Author(s) -
Rapoport Am
Publication year - 1966
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830110103
Subject(s) - task (project management) , sort , decision maker , dynamic decision making , computer science , control (management) , business decision mapping , decision field theory , decision engineering , operations research , decision analysis , optimal decision , affect (linguistics) , management science , dynamic programming , artificial intelligence , decision support system , decision tree , mathematics , psychology , engineering , mathematical economics , algorithm , communication , systems engineering , information retrieval
Abstract Models of decision making can be grouped into two general classes: static and dynamic decision making. The first consists of those tasks where a single decision is made, the subject is told of the results of his decision, and no further application is made. In dynamic decision making, subsequent decisions depend in part on past experience in the task and thus learning is involved in the act. The latter sort of decisions can be further broken down into two types: those that do not affect the environment in which the decision maker is behaving, and those involving the future environment. A decision maker who can actively manipulate the environment by his decisions is conceived of as a controller. This article considers a dynamic programming model for this type of decision‐making task.