scholarly journals Algorithmic Risk Assessments Can Alter Human Decision-Making Processes in High-Stakes Government Contexts

2021 ◽  
Vol 5 (CSCW2) ◽  
pp. 1-33
Author(s):  
Ben Green ◽  
Yiling Chen
Keyword(s):  
Decision Making ◽  
Risk Assessments ◽  
High Stakes ◽  
Human Decision ◽  
Decision Making Processes

scholarly journals Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

2019 ◽  
Vol 23 (5) ◽  
pp. 2261-2278 ◽  
Author(s):  
Jin-Young Hyun ◽  
Shih-Yu Huang ◽  
Yi-Chen Ethan Yang ◽  
Vincent Tidwell ◽  
Jordan Macknick
Keyword(s):  
Decision Making ◽  
Risk Perception ◽  
Regional Scale ◽  
Agent Based ◽  
Natural Processes ◽  
Complex Adaptive ◽  
San Juan River ◽  
Human Decision ◽  
Decision Making Processes ◽  
Engineered Systems

Abstract. Managing water resources in a complex adaptive natural–human system is a challenge due to the difficulty of modeling human behavior under uncertain risk perception. The interaction between human-engineered systems and natural processes needs to be modeled explicitly with an approach that can quantify the influence of incomplete/ambiguous information on decision-making processes. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) to address this challenge. The human decision-making processes is described in the ABM using Bayesian inference (BI) mapping joined with a cost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's psychological thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. A risk perception parameter is used in the BI mapping to represent an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River basin in New Mexico, USA, to demonstrate the utility of this method. The calibrated BC-ABM–RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that do not take risk perception into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost of agent's decision, and upscaling the watershed ABM to the regional scale.

Cognitive Model of Team Collaboration: Macro-Cognitive Focus

2005 ◽  
Vol 49 (3) ◽  
pp. 269-273 ◽  
Author(s):  
Norman Warner ◽  
Michael Letsky ◽  
Michael Cowen
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Empirical Data ◽  
Cognitive Model ◽  
Distributed Teams ◽  
Descriptive Model ◽  
Team Collaboration ◽  
Face To Face ◽  
Human Decision ◽  
Decision Making Processes

The purpose of this paper is to describe a cognitive model of team collaboration emphasizing the human decision-making processes used during team collaboration. The descriptive model includes the domain characteristics, collaboration stages, meta- and macro cognitive processes and the mechanisms for achieving the stages and cognitive processes. Two experiments were designed to provide empirical data on the validity of the collaboration stages and cognitive processes of the model. Both face-to-face and asynchronous, distributed teams demonstrated behavior that supports the existence of the collaboration stages along with seven cognitive processes.

scholarly journals A Review: Artificial Intelligent Approach for Enhancing Adaptability in an Adaptive E-Learning Environment

2021 ◽  
Vol 10 (4) ◽  
pp. 37-42
Author(s):  
M.P.L. Perera
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Artificial Intelligent ◽  
Human Decision ◽  
Decision Making Processes ◽  
E Learning ◽  
Intelligent Approach ◽  
Learning Frameworks

Adaptive e-learning the aim is to fill the gap between the pupil and the educator by discussing the needs and skills of individual learners. Artificial intelligence strategies that have the potential to simulate human decision-making processes are important around adaptive e-Learning. This paper explores the Artificial techniques; Fuzzy Logic, Neural Networks, Bayesian Networks and Genetic Algorithms, highlighting their contributions to the notion of the adaptability in the sense of Adaptive E-learning. The implementation of Artificial Neural Networks to resolve problems in the current Adaptive e-learning frameworks have been established.

scholarly journals A Hesitant Fuzzy Envelope Based Expert System in Human Decision Making

2021 ◽  
Vol 2 (1) ◽  
pp. 1-6
Author(s):  
Panjkaj Srivastava ◽  
Rajkrishna Mondal
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Making Process ◽  
Individual Decision ◽  
Decision Style ◽  
Human Decision ◽  
Decision Making Processes ◽  
Linguistic Approach

Naturally, individual decision style is qualitative rather than quantitative settings. In nature, the human way of thinking is uncertain and fuzziness that demands the use of the linguistic approach of problems related to the decision. The group decision making process is highly affected by hesitant situations among the members for clarity-based decisions. In order to remove the hesitant situations, the proposed Hesitant Fuzzy Envelope expert system provides the group decision making processes with more realistic output in envelope form rather than CRISP one. In this study, we shall discuss a linguistic based expert system that will help to make more realistic decisions in a hesitant situation by using Hesitant Fuzzy Envelope technique.

Implementation of an Intelligent Model for Decision Making Based on CBR for Supply Chain Solution in Retail for a Cluster of Supermarkets

2019 ◽  
pp. 381-397
Author(s):  
Adrian F. Loera-Castro ◽  
Jaime Sanchez ◽  
Jorge Restrepo ◽  
Angel Fabián Campoya Morales ◽  
Julian I. Aguilar-Duque
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Intelligent Systems ◽  
Case Based Reasoning ◽  
Human Beings ◽  
Human Decision ◽  
Decision Making Processes ◽  
A Chain ◽  
The Times ◽  
Intelligent Model

The latter includes customizing the user interface, as well as the way the system retrieves and processes cases afterward. The resulting cases may be shown to the user in different ways, and/or the retrieved cases may be adapted. This chapter is about an intelligent model for decision making based on case-based reasoning to solve the existing problem in the planning of distribution in the supply chain between a distribution center and a chain of supermarkets. First, the authors mentioned the need for intelligent systems in the decision-making processes, where they are necessary due to the limitations associated with conventional human decision-making processes. Among them, human experience is very scarce, and humans get tired of the burden of physical or mental work. In addition, human beings forget the crucial details of a problem, and many of the times are inconsistent in their daily decisions.

scholarly journals Optimization of the Casualties’ Treatment Process: Blended Military Experiment

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 706
Author(s):  
Jan Hodický ◽  
Dalibor Procházka ◽  
Roman Jersák ◽  
Petr Stodola ◽  
Jan Drozd
Keyword(s):  
Decision Making ◽  
Medical Treatment ◽  
Process Model ◽  
Deterministic Model ◽  
Dynamics Simulation ◽  
Computer Assisted ◽  
Decision Making Factors ◽  
Human Decision ◽  
Simulation Paradigm ◽  
Decision Making Processes

At the battalion level, NATO ROLE1 medical treatment command focuses on the provision of primary health care being the very first physician and higher medical equipment intervention for casualty treatments. ROLE1 has paramount importance in casualty reductions, representing a complex system in current operations. This study deals with an experiment on the optimization of ROLE1 according to the key parameters of the numbers of physicians, the number of ambulances and the distance between ROLE1 and the current battlefield. The very first step in this study is to design and implement a model of current battlefield casualties. The model uses friction data generated from an already executed computer assisted exercise (CAX) while employing a constructive simulation to produce offense and defense scenarios on the flow of casualties. The next step in the study is to design and implement a model representing the transportation to ROLE1, its structure and behavior. The deterministic model of ROLE1, employing a system dynamics simulation paradigm, uses the previously generated casualty flows as the inputs representing human decision-making processes through the recorder CAX events. A factorial experimental design for the ROLE1 model revealed the recommended variants of the ROLE1 structure for both offensive and defensive operations. The overall recommendation is for the internal structure of ROLE1 to have three ambulances and three physicians for any kind of current operation and any distance between ROLE1 and the current battlefield within the limit of 20 min. This study provides novelty in the methodology of casualty estimations involving human decision-making factors as well as the optimization of medical treatment processes through experimentation with the process model.

scholarly journals Risk-Sensitive Multiagent Decision-Theoretic Planning Based on MDP and One-Switch Utility Functions

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Wei Zeng ◽  
Hongtao Zhou ◽  
Mingshan You
Keyword(s):  
Decision Making ◽  
Attitude Change ◽  
Optimal Policy ◽  
Risk Attitude ◽  
High Stakes ◽  
Group Settings ◽  
Risk Sensitive ◽  
Markov Decision ◽  
Decision Making Processes ◽  
Initial Wealth

In high stakes situations decision-makers are often risk-averse and decision-making processes often take place in group settings. This paper studies multiagent decision-theoretic planning under Markov decision processes (MDPs) framework with considering the change of agent’s risk attitude as his wealth level varies. Based on one-switch utility function that describes agent’s risk attitude change with his wealth level, we give the additive and multiplicative aggregation models of group utility and adopt maximizing expected group utility as planning objective. When the wealth level approaches infinity, the characteristics of optimal policy are analyzed for the additive and multiplicative aggregation model, respectively. Then a backward-induction method is proposed to divide the wealth level interval from negative infinity to initial wealth level into subintervals and determine the optimal policy in states and subintervals. The proposed method is illustrated by numerical examples and the influences of agent’s risk aversion parameters and weights on group decision-making are also analyzed.

Implementation of an Intelligent Model for Decision Making Based on CBR for Supply Chain Solution in Retail for a Cluster of Supermarkets

2021 ◽  
pp. 1224-1240
Author(s):  
Adrian F. Loera-Castro ◽  
Jaime Sanchez ◽  
Jorge Restrepo ◽  
Angel Fabián Campoya Morales ◽  
Julian I. Aguilar-Duque
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Intelligent Systems ◽  
Case Based Reasoning ◽  
Human Beings ◽  
Human Decision ◽  
Decision Making Processes ◽  
A Chain ◽  
The Times ◽  
Intelligent Model

The latter includes customizing the user interface, as well as the way the system retrieves and processes cases afterward. The resulting cases may be shown to the user in different ways, and/or the retrieved cases may be adapted. This chapter is about an intelligent model for decision making based on case-based reasoning to solve the existing problem in the planning of distribution in the supply chain between a distribution center and a chain of supermarkets. First, the authors mentioned the need for intelligent systems in the decision-making processes, where they are necessary due to the limitations associated with conventional human decision-making processes. Among them, human experience is very scarce, and humans get tired of the burden of physical or mental work. In addition, human beings forget the crucial details of a problem, and many of the times are inconsistent in their daily decisions.

An Integrated AFS-Based SWOT Analysis Approach for Evaluation of Strategies Under MCDM Environment

2018 ◽  
Vol 1 (2) ◽  
pp. 129-147 ◽  
Author(s):  
Sunil Pratap Singh ◽  
Preetvanti Singh
Keyword(s):  
Decision Making ◽  
Swot Analysis ◽  
Analytic Hierarchy ◽  
Real World Application ◽  
Normalization Methods ◽  
Human Decision ◽  
Decision Making Processes ◽  
Simple Additive Weighting ◽  
Hierarchy Process ◽  
Afs Theory

This article outlines the development of a hybrid methodology aimed to help the policymakers in strategic planning. The proposed methodology integrates the axiomatic fuzzy set (AFS) theory, analytic hierarchy process (AHP), and the concept of simple additive weighting (SAW) to evaluate the strategies by strengths, weaknesses, opportunities, and threats (SWOT) analysis. The combination of AHP with SWOT yields analytically determined weights of the factors included in SWOT analysis. The SAW technique provides a flexible technique to obtain the final ranking of strategies in multi-criteria decision situations. In SAW, the strategies are described using the AFS-based AHP calculation framework for normalization and consistent ratings over the SWOT factors. The AFS theory is incorporated in the model to overcome the uncertainty and ambiguity in human decision-making processes. The proposed integrated methodology copes with the inconsistency caused by different types of fuzzy numbers and normalization methods required in solving multi-criteria decision-making (MCDM) problems. A real-world application is conducted to illustrate the utilization of the model to evaluate SWOT analysis and strategies for tourism development.

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