scholarly journals Bayesian Analysis of Processed Information in Decision Making Experiments

2019 ◽  
Author(s):  
Tillmann Nett ◽  
Nadine Nett ◽  
Andreas Glöckner
Keyword(s):  
Decision Making ◽  
Bayesian Analysis ◽  
General Model ◽  
Mathematical Framework ◽  
Decision Strategies ◽  
Information Usage ◽  
Recovery Simulation ◽  
Choice Probabilities

In research on decision making, experiments are often analyzed in terms of decision strategies. These decision strategies define both which information is used as well as how it is used. However, often it is desirable to identify the used information without any further assumptions about how it is used. We provide a mathematical framework that allows analyzing which information is used by identifying consistent patterns on the choice probabilities. This framework makes it possible to generate the most general model consistent with an information usage hypothesis and then to test this model against others. We test our approach in a recovery simulation to show thatthe used information may be reliably identified AUC>= .90. In addition, to further verify the correctness we compare our approach with other approaches based on strategy fitting to show that both produce similar results.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

scholarly journals Optimal Policies for Quantum Markov Decision Processes

2021 ◽  
Author(s):  
Ming-Sheng Ying ◽  
Yuan Feng ◽  
Sheng-Gang Ying
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Quantum Systems ◽  
Sequential Decision Making ◽  
Mathematical Framework ◽  
Sequential Decision ◽  
Learning Techniques ◽  
Optimal Policies ◽  
Markov Decision ◽  
Programming Algorithms

AbstractMarkov decision process (MDP) offers a general framework for modelling sequential decision making where outcomes are random. In particular, it serves as a mathematical framework for reinforcement learning. This paper introduces an extension of MDP, namely quantum MDP (qMDP), that can serve as a mathematical model of decision making about quantum systems. We develop dynamic programming algorithms for policy evaluation and finding optimal policies for qMDPs in the case of finite-horizon. The results obtained in this paper provide some useful mathematical tools for reinforcement learning techniques applied to the quantum world.

Estimating Choice Probabilities in Multiattribute Decision Making

1981 ◽  
Vol 8 (1) ◽  
pp. 76 ◽  
Author(s):  
Paul E. Green ◽  
J. Douglas Carroll ◽  
Wayne S. DeSarbo
Keyword(s):  
Decision Making ◽  
Choice Probabilities

Ties that Bind?

1998 ◽  
Vol 31 (1) ◽  
pp. 45-71 ◽  
Author(s):  
WILL H. MOORE ◽  
DAVID R. DAVIS
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
General Model ◽  
International Conflict ◽  
Conflict Behavior ◽  
Structural Constraints ◽  
Structural Factors ◽  
International Interactions ◽  
The Impact

In this article, the authors develop and empirically evaluate a general model of the linkages between domestic and international conflict behavior. Much of the literature on domestic international interactions has focused on the structural constraints of the international and domestic systems on leaders' foreign policy decisions. Rather than focusing on structural constraints, the present authors model the influence of the behavior of domestic and international rivals on leader decision making. The impact of rivals' behavior on conflict across the domestic-international nexus has been neglected relative to the role of structural factors. This study helps redress that imbalance. The authors test their model with a statistical analysis of Zaire during the period 1975 to 1992 and find substantial support for the model.

scholarly journals An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study

2018 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Jiyong Ding ◽  
Juefang Cai ◽  
Guangxiang Guo ◽  
Chen Chen
Keyword(s):  
Decision Making ◽  
Bayesian Analysis ◽  
Emergency Management ◽  
Utility Theory ◽  
Urban Traffic ◽  
Economic Losses ◽  
Water Logging ◽  
Multi Attribute Utility Theory ◽  
Emergency Decision Making ◽  
Emergency Decision

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.

scholarly journals Parallel Constraint Satisfaction in Memory-Based Decisions

2011 ◽  
Vol 58 (3) ◽  
pp. 180-195 ◽  
Author(s):  
Andreas Glöckner ◽  
Sara D. Hodges
Keyword(s):  
Decision Making ◽  
Constraint Satisfaction ◽  
Information Integration ◽  
Time Pressure ◽  
Human Information Processing ◽  
Decision Task ◽  
Equal Weight ◽  
Decision Strategies ◽  
Simple Heuristics ◽  
Decision Times

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

How Well Do E-Commerce Web Sites Support Compensatory and Non-Compensatory Decision Strategies? An Exploratory Study

2011 ◽  
pp. 1592-1607
Author(s):  
Naveen Gudigantala ◽  
Jaeki Song ◽  
Donald R. Jones
Keyword(s):  
Decision Making ◽  
Web Sites ◽  
Exploratory Study ◽  
Decision Quality ◽  
Consumer Decision Making ◽  
Online Retailing ◽  
Compensatory Strategies ◽  
Decision Strategies ◽  
Web Based ◽  
Levels Of Support

The burgeoning growth of online retailing is forcing businesses to provide better support for consumer decision making on e-commerce Web sites. Consequently, researchers in information systems and marketing have been focusing on investigating the effectiveness of Web-based decision support systems (WebDSS) in providing accurate and satisfying choices for customers. We consider WebDSS implementation based on compensatory, non-compensatory decision strategies and synthesize the existing literature. The results of synthesis show that compensatory WebDSS perform better than non-compensatory WebDSS in terms of decision quality, satisfaction, effort, and confidence. We then investigate the level of Web site support provided for consumers’ execution of compensatory and non-compensatory strategies. We examined 375 U.S.-based company Web sites and found that though moderate levels of support exists for consumers to implement non-compensatory choice strategies, virtually no support exists for executing multi-attribute-based compensatory choice strategies.

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