Term Expectation and Uncertainty in Human Decision Behavior

Term Expectation and Uncertainty in Human Decision Behavior PDF Author: Jerry D. Tate
Publisher:
ISBN:
Category :
Languages : en
Pages : 28

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Term Expectation and Uncertainty in Human Decision Behavior

Term Expectation and Uncertainty in Human Decision Behavior PDF Author: Jerry D. Tate
Publisher:
ISBN:
Category :
Languages : en
Pages : 28

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Book Description


Term Expectation and Uncertainty in Human Decision Behavior

Term Expectation and Uncertainty in Human Decision Behavior PDF Author: Jerry D. Tate
Publisher:
ISBN:
Category :
Languages : en
Pages : 18

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Book Description
This study was conducted to investigate the manner and degree to which a decision makers sequence of decisions is influenced by objectives of varying remoteness (term expectation) and by informational uncertainty. The effects of these two variables on sequential decision performance were studied in a 4 x 4 factorial experiment. Term expectation was defined as the number of problems over which the decision maker accumulated his score. Uncertainty was manipulate by controlling the number of events from which the subject was to predict a terminal event. Decisions (predictions) were made either at prescribed uncertainty levels or on a freely chosen basis (depending on the prevailing experimental conditions), and a range of choices varying in degree of risk and payoff was available at each uncertainty level. The same five subjects served in all conditions of the experiment. Choices were evaluated in terms of risk, expected value, and average departure from linear progression to mean winning score (DFL). No significant differences were obtained for term expectation, per se. Maximum expected values were achieved at intermediate levels of uncertainty. (Author).

Term Expectation and Uncertainty in Human Decision Behavior

Term Expectation and Uncertainty in Human Decision Behavior PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
This study was conducted to investigate the manner and degree to which a decision makers sequence of decisions is influenced by objectives of varying remoteness (term expectation) and by informational uncertainty. The effects of these two variables on sequential decision performance were studied in a 4 x 4 factorial experiment. Term expectation was defined as the number of problems over which the decision maker accumulated his score. Uncertainty was manipulate by controlling the number of events from which the subject was to predict a terminal event. Decisions (predictions) were made either at prescribed uncertainty levels or on a freely chosen basis (depending on the prevailing experimental conditions), and a range of choices varying in degree of risk and payoff was available at each uncertainty level. The same five subjects served in all conditions of the experiment. Choices were evaluated in terms of risk, expected value, and average departure from linear progression to mean winning score (DFL). No significant differences were obtained for term expectation, per se. Maximum expected values were achieved at intermediate levels of uncertainty. (Author).

Completing the Forecast

Completing the Forecast PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309180538
Category : Science
Languages : en
Pages : 124

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Book Description
Uncertainty is a fundamental characteristic of weather, seasonal climate, and hydrological prediction, and no forecast is complete without a description of its uncertainty. Effective communication of uncertainty helps people better understand the likelihood of a particular event and improves their ability to make decisions based on the forecast. Nonetheless, for decades, users of these forecasts have been conditioned to receive incomplete information about uncertainty. They have become used to single-valued (deterministic) forecasts (e.g., "the high temperature will be 70 degrees Farenheit 9 days from now") and applied their own experience in determining how much confidence to place in the forecast. Most forecast products from the public and private sectors, including those from the National Oceanographic and Atmospheric Administration's National Weather Service, continue this deterministic legacy. Fortunately, the National Weather Service and others in the prediction community have recognized the need to view uncertainty as a fundamental part of forecasts. By partnering with other segments of the community to understand user needs, generate relevant and rich informational products, and utilize effective communication vehicles, the National Weather Service can take a leading role in the transition to widespread, effective incorporation of uncertainty information into predictions. "Completing the Forecast" makes recommendations to the National Weather Service and the broader prediction community on how to make this transition.

U.S. Government Research Reports

U.S. Government Research Reports PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 2180

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Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports PDF Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 252

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Book Description


Decision Making Under Uncertainty

Decision Making Under Uncertainty PDF Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350

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Book Description
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Decision Making under Uncertainty

Decision Making under Uncertainty PDF Author: Kerstin Preuschoff
Publisher: Frontiers Media SA
ISBN: 2889194663
Category : Biological psychiatry
Languages : en
Pages : 144

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Book Description
Most decisions in life are based on incomplete information and have uncertain consequences. To successfully cope with real-life situations, the nervous system has to estimate, represent and eventually resolve uncertainty at various levels. A common tradeoff in such decisions involves those between the magnitude of the expected rewards and the uncertainty of obtaining the rewards. For instance, a decision maker may choose to forgo the high expected rewards of investing in the stock market and settle instead for the lower expected reward and much less uncertainty of a savings account. Little is known about how different forms of uncertainty, such as risk or ambiguity, are processed and learned about and how they are integrated with expected rewards and individual preferences throughout the decision making process. With this Research Topic we aim to provide a deeper and more detailed understanding of the processes behind decision making under uncertainty.

Judgment Under Uncertainty

Judgment Under Uncertainty PDF Author: Daniel Kahneman
Publisher: Cambridge University Press
ISBN: 9780521284141
Category : Psychology
Languages : en
Pages : 574

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Book Description
Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.

Decisions, Uncertainty, and the Brain

Decisions, Uncertainty, and the Brain PDF Author: Paul W. Glimcher
Publisher: MIT Press
ISBN: 9780262572279
Category : Medical
Languages : en
Pages : 404

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Book Description
In this provocative book, Paul Glimcher argues that economic theory may provide an alternative to the classical Cartesian model of the brain and behavior. Glimcher argues that Cartesian dualism operates from the false premise that the reflex is able to describe behavior in the real world that animals inhabit. A mathematically rich cognitive theory, he claims, could solve the most difficult problems that any environment could present, eliminating the need for dualism by eliminating the need for a reflex theory. Such a mathematically rigorous description of the neural processes that connect sensation and action, he explains, will have its roots in microeconomic theory. Economic theory allows physiologists to define both the optimal course of action that an animal might select and a mathematical route by which that optimal solution can be derived. Glimcher outlines what an economics-based cognitive model might look like and how one would begin to test it empirically. Along the way, he presents a fascinating history of neuroscience. He also discusses related questions about determinism, free will, and the stochastic nature of complex behavior.