Computational models are like the new kids in town for the field of decision making. This field is largely dominated by axiomatic utility theories (Bell, Raiffa, & Tversky, 1998; Luce, 2000) or simple heuristic rule models (Gigerenzer, Todd, & the ABC Research Group, 1999; Payne, Bettman, & Johnson, 1993). It is difficult for “the new kids” to break into this field for a very important reason: ...

The stochastic tree is a recently introduced generalization of the decision tree which allows the explicit depiction of temporal uncertainty, while still employing the familiar rollback procedure for decision trees. We offer in this paper an introduction to stochastic tree modeling and techniques involved in their application to medical treatment decisions. We also describe an application of th...

The study of judgment and decision making (JDM) is traditionally concerned with the comparison of judgments to standards, standards that allow evaluation of the judgments as better or worse. I use the term “judgments” to include decisions, which are judgments about what to do. The major standards come from probability theory, utility theory, and statistics. These are mathematical theories or “m...

The sequential probability ratio test (SPRT) and related drift-diffusion model (DDM) are optimal for choosing between two hypotheses using the minimal (average) number of samples and relevant for modeling the decision-making process in human observers. This work extends these models to group decision making. Previous works have focused almost exclusively on group accuracy; here, we explicitly a...

8.1 Two Research Conundrums..................................................................................................134 8.1.1 Lindblom’s Theory of Administrative Incrementalism...........................................134 8.1.2 Wildavsky’s Theory of Budgetary Incrementalism.................................................135 8.1.3 The Diverse Meanings of Budgetary “Incrementalism”.......

This paper analyzes the assumptions of the decision making models in the context of artificial general intelligence (AGI). It is argued that the traditional approaches, exemplified by decision theory and reinforcement learning, are inappropriate for AGI, because their fundamental assumptions on available knowledge and resource cannot be satisfied here. The decision making process in the AGI sys...

A number of simulation techniques may be applied to strategy and decision-making. In using such techniques it is important to understand the role of models, in the context of the wider decision-making process which is largely a communal and political process; the choice of a particular approach or technique depends not only on the type of decision being considered, but also on the stage of the ...

This paper investigates alternative approaches to constant rate discounting for calculation of Net Present Value (NPV) in life cycle cost models that are used for engineering trade studies. Alternative approaches are necessary to meet the challenge of equitable intergenerational resource allocation for projects like radioactive waste disposal that have a life cycle that impacts future generatio...

Bounded by limited cognitive capabilities, decision-makers resort to using mental models (reduced versions of real world dynamics) for decision-making and interventions in complex tasks. Such mental models are constantly updated with new experience and knowledge acquired, facilitating a learning process. Through this learning process, mental models can be refined to better represent real world ...