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(Sub) Optimality and (non) optimal satisficing in risky decision experiments

Daniela Di Cagno, Arianna Galliera, Werner Güth, Francesca Marzo, Noemi Pace
2017 Theory and Decision  
By incentivizing aspiration formation, we can test satisficing, and in cases of satisficing, determine whether it is optimal.  ...  , i.e., by forming aspirations and checking for satisficing before making their choice.  ...  Figure 7 presents the evidence of "burning money" and "committing suicide" for all data (both phases of both treatments), as well the consequences for the chances to earn e14, where the left (right) diagram  ... 
doi:10.1007/s11238-017-9591-2 fatcat:sdbz5kxltfhkrpaqf6zr52j6ke

Risk as Challenge: A Dual System Stochastic Model for Binary Choice Behavior [article]

Samuel Shye, Ido Haber
2019 arXiv   pre-print
The study presents a new model for predicting the popularity of choices made in binary risk problems.  ...  The novelty of the CT perspective as a new paradigm is illuminated by its simple, single-index (CI) representation of psychological effects proposed by Prospect Theory for describing choice behavior (certainty  ...  However, our evidence for the optimal number of free parameters is not conclusive and the simpler model of three parameters, a, γ, δ (i.e. a0=a1), for gains and three, a', γ', δ', (i.e. a'0=a'1), for losses  ... 
arXiv:1910.04487v1 fatcat:yg4hcbskinav3bnec73gnltt64

Computing rank dependent utility in graphical models for sequential decision problems

Gildas Jeantet, Olivier Spanjaard
2011 Artificial Intelligence  
The computation of an optimal strategy for a given representation and a given decision criterion is then an algorithmic issue in itself.  ...  Specifically, we present algorithms for solving decision tree models and influence diagram models of sequential decision problems.  ...  Two Approaches for Computing RDU We propose here two approaches for determining an RDU-optimal strategy in a decision tree.  ... 
doi:10.1016/j.artint.2010.11.019 fatcat:z43rupbpc5h4bgfdlmitjp5tea

Language-Driven Engineering: From General-Purpose to Purpose-Specific Languages [chapter]

Bernhard Steffen, Frederik Gossen, Stefan Naujokat, Tiziana Margaria
2019 Lecture Notes in Computer Science  
to optimally capture the mindsets of the involved stakeholders.  ...  In this paper, we present the paradigm of Language-Driven Engineering (LDE), which is characterized by its unique support for division of labour on the basis of Domain-Specific Languages (DSLs) targeting  ...  Binary decision diagrams [30] (BDDs), the level 3 components of Fig. 5 , are a common graphical language for decision modeling.  ... 
doi:10.1007/978-3-319-91908-9_17 fatcat:5n4ju6uhszgepaq5yo6a5zsduy

Linear-Nonlinear-Poisson Models of Primate Choice Dynamics

Greg S Corrado, Leo P Sugrue, H Sebastian Seung, William T Newsome
2005 Journal of The Experimental Analysis of Behavior  
In our experiments, 2 rhesus monkeys (Macacca mulatta) foraged for juice rewards by making eye movements to one of two colored icons presented on a computer monitor, each rewarded on dynamic variable-interval  ...  Using a generalization of Wiener kernel analysis, we recover a compact mechanistic description of the impact of past reward on future choice in the form of a Linear-Nonlinear-Poisson model.  ...  The LNP framework, diagrammed in Figure 3 , consists of three serial feed-forward computational stages.  ... 
doi:10.1901/jeab.2005.23-05 pmid:16596981 pmcid:PMC1389782 fatcat:x2nckx6lsna2zp4dj2d7jkqciy

A Python-based multicriteria portfolio selection DSS

Panos Xidonas, Haris Doukas, Elissaios Sarmas
2020 Reserche operationelle  
After the cumulative integration of the results, a series of mathematical programming models are applied in the sec- ond phase, that of multicriteria portfolio optimization; a mixed-integer quadratic programming  ...  Our purpose in this article is to develop an integrated portfolio management decision support system, which takes into account the inherent multidimensional nature of the problem, while allowing the decision  ...  The model is equipped with both continuous and binary decision variables.  ... 
doi:10.1051/ro/2020140 fatcat:ykc7x3g6cngsjnfflpm3g6zase

Improved ant colony optimization for quantum cost reduction

Shaveta Thakral, Dipali Bansal
2020 Bulletin of Electrical Engineering and Informatics  
Therefore post synthesis optimization needs to be done for reduction of quantum cost.  ...  The main goal of this paper is to propose improved ant colony optimization (ACO) algorithm for quantum cost reduction.  ...  Binary decision diagram based synthesis approach is proved to be ancilla free and can be used for large number of variables [20] .  ... 
doi:10.11591/eei.v9i4.1657 fatcat:ffsxg37aqbairmmxzqlemifia4

History and Potential of Binary Segmentation for Exploratory Data Analysis

James N. Morgan
2021 Journal of Data Science  
The restrictive assumptions of linearity and additivity of effects as in regression are no longer necessary to save degrees of freedom.  ...  Where there is a clear criterion (dependent) variable or classification, sequential binary segmentation (tree) programs are being used.  ...  Acknowledgement The first AID program was the contribution of John Sonquist and Elizabeth  ... 
doi:10.6339/jds.2005.03(2).198 fatcat:z35y3m6llnhypcuwydttosfe2e

Core Model of the Forestry Investment Project Decision Support System Based on the Real Option

Yang cheng, Zhang shaowen
2016 International Journal of Multimedia and Ubiquitous Engineering  
is suitable for the forestry project and then to design a decision support system which is suitable for forestry investment project.  ...  The traditional forestry investment project evaluation mostly adopts the net present value method, and ignores option property of the forestry investment project, which is easy to cause the decision-making  ...  Last but not the least, my gratitude also extends to my family who have been assisting, supporting and caring for me all of my life.  ... 
doi:10.14257/ijmue.2016.11.3.28 fatcat:ndiituqrsfdnxptn5v7f3b7lg4

Automatic discovery of interpretable planning strategies

Julian Skirzyński, Frederic Becker, Falk Lieder
2021 Machine Learning  
One of the biggest remaining obstacles to leveraging the aforementioned methods for improving human decision-making is that the policies they learn are opaque to people.  ...  three different classes of sequential decision problems.  ...  To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.  ... 
doi:10.1007/s10994-021-05963-2 fatcat:zyet6jmrrbhihle6feexwge26m

Computational Intelligence-Based Diagnosis Tool for the Detection of Prediabetes and Type 2 Diabetes in India

Shankaracharya, Devang Odedra, Subir Samanta, Ambarish S. Vidyarthi
2012 The Review of Diabetic Studies  
The incidence of diabetes is increasing rapidly across the globe. India has the highest proportion of diabetic patients, earning it the doubtful distinction of the 'diabetes capital of the world'.  ...  Different combinations and numbers of hidden nodes and expectation maximization (EM) iterations were used to optimize the accuracy of the algorithm.  ...  Undoubtedly, the evaluation of data taken from patients, and experts' decisions, are critical for diagnosis.  ... 
doi:10.1900/rds.2012.9.55 pmid:22972445 pmcid:PMC3448174 fatcat:ztjswko3sndhxiuy34s4wkl5ri

Finding nearest facility for multiple customers using voronoi diagram

Ravi Agarwal, Deepak Garg
2014 2014 IEEE International Advance Computing Conference (IACC)  
For the decision of the facility location, outer algorithm is optimized and inner algorithm is optimized for the allocation of customer's demand under the given decision of the outer algorithm.The hierarchical  ...  For the facility location optimization problems, which has earned extensive research interests, Maximal covering location problem (MCLP) is one of the well-known model.  ... 
doi:10.1109/iadcc.2014.6779399 fatcat:loz3q7gjtfcwlhoceew25uauva

A computational theory of decision networks

Nevin Lianwen Zhang, Runping Qi, David Poole
1994 International Journal of Approximate Reasoning  
Decision networks inherit the advantages of both influence diagrams and Markov decision processes, which makes them a better representation framework for decision analysis, planning under uncertainty,  ...  The theme of this paper is to seek the weakest condition under which decision networks are stepwise-solvable and to seek the best algorithms for evaluating stepwise-solvable decision networks.  ...  ACKNOWLEDGEMENTS The first author would like to thank Glenn Shafer and Prakash Shenoy for getting him interested in this area of research and for their comments on this paper.  ... 
doi:10.1016/0888-613x(94)90026-4 fatcat:u6ly7dhabzaz3pxw6lqggwye4y

Menus of Contracts Determine Sorting Patterns

Mark Bernard, Thomas Dohmen, Arjan Non, Ingrid Rohde
2019 Journal of Economic Psychology  
If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User  ...  Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of  ...  The table shows for each binary menu of contracts the key characteristics of workers who sort into a particular payment scheme.  ... 
doi:10.1016/j.joep.2019.04.004 fatcat:kg663u7lobc6hpkl4xvbwmkqa4

Dynamic iteration stopping algorithm for non-binary LDPC-coded high-order PRCPM in the Rayleigh fading channel

Rui Xue, Yanbo Sun, Qiang Wei
2016 EURASIP Journal on Wireless Communications and Networking  
Two dynamic iterative stopping algorithms, namely, cross entropy and hard decision aided combined with weighted extrinsic information exchange for cases with medium and high SNRs, are then proposed.  ...  Theoretic analysis and simulation results for the Rayleigh fading channel show that the combination of weighted extrinsic information exchange and the two dynamic iterative stopping algorithms effectively  ...  However, not all received sequences have optimal decoding results at the same number of iterations. For several specific sequences, error-free decoding can be achieved by a few iterations.  ... 
doi:10.1186/s13638-016-0562-z fatcat:w7423hdy5bgexfsoazjyaiffe4
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