scholarly journals A Satisficing Heuristic Decision-Making Model under Limited Attention and Incomplete Preferences

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xinlin Wu ◽  
Daoxin Ding
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Choice Theory ◽  
Time Pressure ◽  
Choice Model ◽  
Incomplete Preferences ◽  
Limited Attention ◽  
Limited Information ◽  
Choice Procedure ◽  
Decision Making Model

Classical choice theory assumes that a decision-maker considers all feasible alternatives. However, a decision-maker in the real world can not consider all alternatives because of limited attention. In this paper, we propose a satisficing choice model to describe the choice procedure based on the incomplete preferences under the limited attention of the decision-maker. Moreover, the existence and rationality properties of the satisficing choice model on the different domains are studied combined with some proposed rationality conditions. Further, the proposed satisficing choice model is applied to a case of quality competition. Results show that the satisficing choice model of this paper is of a certain theoretical guiding significance to a kind of emergency decisions made by decision-makers under the circumstance of time pressure and limited information. It can also be the theoretical foundation for the study on the boundedly rational decision-making.

A Crime Decision-Making Model Based on AHP

2011 ◽  
Vol 50-51 ◽  
pp. 885-889 ◽  
Author(s):  
Fei Xue Yan ◽  
Jing Xia ◽  
Guan Qun Shen ◽  
Xu Sheng Kang
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Hazard Rate ◽  
Prediction Models ◽  
Choice Model ◽  
Ahp Method ◽  
Spatial Choice ◽  
Crime Prediction ◽  
Models Comparison ◽  
Decision Making Model

As time goes by, hazard rate of the society would increase if crime prediction was not implemented. Based on objective factors of offenders and victims characteristics, AHP method can be established to get a quantitative and qualitative analysis on crime prediction. Crime prediction is a strategic and tactical measure for crime prevention. According to AHP analysis, two prediction models of the optimal predictive crime locations are put forward. Standard Deviational Ellipses Model and Key Feature adjusted Spatial Choice Model were formulated to account for the anticipated position with various elements from AHP method. These models could be applied in a computer simulation of situation tests of the series murders. Besides, applying those models in certain real case demonstrates how the models work. Through models comparison, the results are summarized that Key Feature adjusted Spatial Choice Model is more conducive in confirming the guilty place. In conclusion, the suggested models, including detailed criminal map, are easy to implement.

A Decision Model for Selecting the Optimum Oil Production Profile Using Multi Criteria Decision Making and Social Choice Theory

2014 ◽  
Author(s):  
Samira Keivanpour ◽  
Hassan Haleh ◽  
Hamed Shakouri Ganjavi
Keyword(s):  
Decision Making ◽  
Social Choice ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Oil Field ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Statistic Model ◽  
Development Plans ◽  
Decision Making Model

Applying a MCDM model has many benefits for decision makers in the course of oil field master development plans preparation and evaluation. In this study, a multi-criteria decision making model is proposed in order to achieve an optimum production profile. The most important criteria and parameters for selection of best production profile are identified. These parameters are derived by several interviews with Iranian oil Industry’s experts. The candidate alternatives for production profile are ranked using a combination of group decision making approach and social choice theory. The degree of group consensus is evaluated by using a statistic model to confirm the validity of decision making model.

An integrated neural network stochastic dynamic programming model for optimizing the operation policy of Aswan High Dam

2011 ◽  
Vol 42 (1) ◽  
pp. 50-67 ◽  
Author(s):  
A. H. El-Shafie ◽  
M. S. El-Manadely
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Dynamic Programming ◽  
Decision Maker ◽  
Stochastic Dynamic Programming ◽  
Programming Model ◽  
Stochastic Dynamic ◽  
Release Policy ◽  
Aswan High Dam ◽  
Decision Making Model

Developing optimal release policies of multipurpose reservoirs is very complex, especially for reservoirs within a stochastic environment. Existing techniques are limited in their ability to represent risks associated with deciding a release policy. The risk aspect of the decisions affects the design and operation of reservoirs. A decision-making model is presented that is capable of replicating the manner in which risks associated with reservoir release decisions are perceived, interpreted and compared by a decision-maker. The model is based on Neural Network (NN) theory. This decision-making model can be used with a Stochastic Dynamic Programming (SDP) approach to produce a NN-SDP model. The resulting integrated model allows the attitudes towards risk of a decision-maker to be considered explicitly in defining the optimal release policy. Clear differences in the policies generated from the basic SDP and the NN-SDP models are observed when examining the operation of Aswan High Dam (AHD). The NN-SDP model yields policies that are more reliable and resilient and less vulnerable than those obtained using the SDP model.

scholarly journals Stochastic representation decision theory: How probabilities and values are entangled dual characteristics in cognitive processes

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243661
Author(s):  
Giuseppe M. Ferro ◽  
Didier Sornette
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Time Pressure ◽  
Rational Expectation ◽  
Weighting Function ◽  
Objective Probability ◽  
Decision Making Process ◽  
Stochastic Representation ◽  
Human Decision ◽  
Expectation Theory

Humans are notoriously bad at understanding probabilities, exhibiting a host of biases and distortions that are context dependent. This has serious consequences on how we assess risks and make decisions. Several theories have been developed to replace the normative rational expectation theory at the foundation of economics. These approaches essentially assume that (subjective) probabilities weight multiplicatively the utilities of the alternatives offered to the decision maker, although evidence suggest that probability weights and utilities are often not separable in the mind of the decision maker. In this context, we introduce a simple and efficient framework on how to describe the inherently probabilistic human decision-making process, based on a representation of the deliberation activity leading to a choice through stochastic processes, the simplest of which is a random walk. Our model leads naturally to the hypothesis that probabilities and utilities are entangled dual characteristics of the real human decision making process. It predicts the famous fourfold pattern of risk preferences. Through the analysis of choice probabilities, it is possible to identify two previously postulated features of prospect theory: the inverse S-shaped subjective probability as a function of the objective probability and risk-seeking behavior in the loss domain. It also predicts observed violations of stochastic dominance, while it does not when the dominance is “evident”. Extending the model to account for human finite deliberation time and the effect of time pressure on choice, it provides other sound predictions: inverse relation between choice probability and response time, preference reversal with time pressure, and an inverse double-S-shaped probability weighting function. Our theory, which offers many more predictions for future tests, has strong implications for psychology, economics and artificial intelligence.

scholarly journals An Essential Analogy Between Coherent Previsions of Random Gains and Well-Behaved Preferences

2019 ◽  
Vol 8 (3) ◽  
pp. 46
Author(s):  
Angelini Pierpaolo ◽  
Angela De Sanctis
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Convex Set ◽  
Choice Model ◽  
Risk Averse ◽  
Two Dimensional ◽  
Unified Approach ◽  
Model Based ◽  
Random Gain ◽  
Economic Criteria

We deal with a unified approach to an integrated and simplified formulation of the decision-making theory in its two subjective components, probability and utility. We show a choice model based on an application of fundamental microeconomic principles to the two-dimensional convex set of all coherent previsions of two random gains. Such a model is well-founded because we find out an analogy between properties of well-behaved preferences and the ones of coherent previsions of random gains. Coherence properties of the notion of price or prevision of a random gain are based on economic criteria of the decision-making theory. In particular, additivity property of price tells us that our decision-maker is not risk-averse but he is risk-neutral. Therefore, the certain gain equivalent to a random gain coincides with a coherent price of this random gain.

scholarly journals A Survey on Entropy and Economic Behaviour

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 157 ◽  
Author(s):  
Ziv Hellman ◽  
Ron Peretz
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Repeated Games ◽  
Natural Extension ◽  
Partial Ordering ◽  
Limited Attention ◽  
Interactive Games ◽  
Economic Behaviour ◽  
The Difference ◽  
Bounded Recall

Entropy plays a significant role in the study of games and economic behaviour in several ways. A decision maker faced with an n-fold repetition of a decision-making problem needs to apply strategies that become increasingly complex as n increases. When several players are involved in selecting strategies in interactive games, bounds on the memories and cognitive capacities of the players can affect possible outcomes. A player who can recall only the last k periods of history is said to have bounded recall of capacity k. We present here a brief survey of results of games played by players with different bounded recall capacities, in particular those indicating surprisingly strong relations between memory and entropy in the study of the min-max values of repeated games with bounded recall. In addition, we consider uses of entropy in measuring the value of information of noisy signal structures, also known as experiments. These are represented by stochastic matrices, with the rows representing states of the world and the columns possible signals. The classic ordering of experiments, due to David Blackwell and based on decision-making criteria, is a partial ordering, which has led to attempts to extend this ordering to a total ordering. If a decision maker has a prior distribution over the states, receipt of a signal yields a posterior. The difference between the entropy of a prior and the expected entropy of the set of possible posteriors has been proposed as a natural extension of the Blackwell ordering. We survey this alongside the theory of rational inattention, which posits that, since individuals have limited attention, they do not always follow every single piece of economic news in planning their economic behaviour. By modelling attention limits as finite channel capacity in the sense of Shannon, economists have developed a theory that explains a range of observed economic behavioural phenomena well.

scholarly journals Multi-Agent Simulation of Individuals’ Escape in the Urban Rainstorm Context Based on Dynamic Recognition-Primed Decision Model

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1190 ◽  
Author(s):  
Qing Yang ◽  
Xu Sun ◽  
Xingxing Liu ◽  
Jinmei Wang
Keyword(s):  
Decision Making ◽  
Time Pressure ◽  
Decision Makers ◽  
Response Strategy ◽  
Limited Information ◽  
Information Gap ◽  
Agent Simulation ◽  
Multi Agent ◽  
Dynamic Recognition ◽  
Classical Decision

The urban rainstorm can evolve into a serious emergency, generally characterized by high complexity, uncertainty, and time pressure. It is often difficult for individuals to find the optimal response strategy due to limited information and time constraints. Therefore, the classical decision-making method based on the “infinite rationality” assumption is sometimes challenging to reflect the reality. Based on the recognition-primed decision (RPD) model, a dynamic RPD (D-RPD) model is proposed in this paper. The D-RPD model assumes that decision-makers can gain experience in the escaping process, and the risk perception of rainstorm disasters can be regarded as a Markov process. The experience of recent attempts would contribute more in decision-making. We design the agent according to the D-RPD model, and employ a multi-agent system (MAS) to simulate individuals’ decisions in the context of a rainstorm. Our results show that experience helps individuals to perform better when they escape in the rainstorm. Recency acts as a one of the key elements in escaping decision making. We also find that filling the information gap between individuals and real-time disaster would help individuals to perform well, especially when individuals tend to avoid extreme decisions.

scholarly journals Influence Analysis in Consensus Search — A Multi Criteria Group Decision Making Approach in Environmental Management

2016 ◽  
Vol 15 (04) ◽  
pp. 791-813 ◽  
Author(s):  
Jorge Ivan Romero-Gelvez ◽  
Monica Garcia-Melon
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Similarity Measures ◽  
Decision Makers ◽  
Final Decision ◽  
Analytic Hierarchy ◽  
Decision Making Model ◽  
Environmental Decision

The environmental decision problems often are divisive, even in a technical realm, decision makers with strong personalities influence outcomes. The purpose of this study is to define and quantify the factors that affect the conservation objectives of a national natural park located in Colombia, South America adding the judgments of six decision makers with different knowledge (every decision maker is also a stakeholder representative). This paper uses a hybrid multiple criteria group decision-making model (MCDM), combining the social network analysis (SNA), analytic hierarchy process (AHP) and similarity measures to solve the consensus and anchoring problem among environmental decision makers. The SNA technique is used to build an influential network relation map among decision makers and to obtain their weights for applying a weighted AHP. Then, the final decision matrices for every decision maker are compared between them in order to identify the consensus level of the problem.

Revisiting the role of process incentives as a determinant of university students’ protest

2012 ◽  
Vol 5 (2) ◽  
pp. 225-253
Author(s):  
Elias Dinas ◽  
Kostas Gemenis
Keyword(s):  
Decision Making ◽  
Collective Action ◽  
Rational Choice ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
Choice Model ◽  
Cost Benefit ◽  
Original Data ◽  
Decision Making Process ◽  
The Public

Drawing on the original data collected during a period of university student protest in Greece, we explore whether the expected gains from the act of protesting itself influence an individual's decision to participate in collective action. More particularly, we investigate the extent to which the process incentives qualify the weight individuals attach to the primary elements of the original cost–benefit equation of rational choice theory as well as other considerations in their decision-making process. Our findings point out that the magnitude of the effect of the process incentives is very strong and its inclusion in a rational choice model improves our understanding of students’ participation in protest activities. Turning to indirect effects, we show that process incentives behave as a first stage precondition for the students’ decision to participate in collective action. In the absence of perceived benefits associated with the process of protesting, the importance of attaining the public good becomes much less important in their decision-making process.

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