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Decision making using minimization of regret

Ronald R. Yager
2004 International Journal of Approximate Reasoning  
We are concerned with the problem of uncertain decision making. The paradigm of decision making using minimization of maximal regret (MMR) is introduced.  ...  We compare this technique with the classic Max-Min valuation method of decision making. We discuss a generalization of the MMR method leading to a parameterized family of minimal regret methods.  ...  Conclusion We are concerned with the problem of uncertain decision making. We described the paradigm of decision making using minimization of maximal regret (MMR).  ... 
doi:10.1016/j.ijar.2003.10.003 fatcat:ke6aqdfeljbipkjfxlpxtqfe5q

A Fuzzy Logic Decision Making Of Student Performance Using Minimization of Weighted Regret Method

2019 International Journal of Engineering and Advanced Technology  
We have proposed a fuzzy decision making approach called Minimization of regret method(MMR) with the Weighted Average (OWA) operator known as MWR approach for making a decision to find in which part of  ...  With these large databases of records of the student, the experts would feel difficult to make a decision, since they cannot judge or decide a student understanding just by the paper test because some  ...  C.PROPOSED WORK: Minimization of regret (MWR) for decision making: Minimization of regret decision making was introduced by savage and made widely applicable by yager and is done by OWA (Ordered weighted  ... 
doi:10.35940/ijeat.f8312.088619 fatcat:um4d6niwunb6plcouxqn474d7y

Decision making on E-waste management methods using minimization of regret with interval-valued intuitionistic fuzzy sets

Martin Nivetha, Pandiammal P., Ramila Gandhi N.
2020 Malaya Journal of Matematik  
To derive an optimal solution, the method of minimization of regret with inter-valued intuitionistic fuzzy sets is used to design a decision making model.  ...  The impact of imposing such canons have made the industries to adopt several methods of managing E-waste and this is the root of chaos in the decision making process on compatible methods of waste management  ...  Decision making on E-waste management methods using minimization of regret with interval-valued intuitionistic fuzzy sets -224/224  ... 
doi:10.26637/mjm0801/0037 fatcat:fxczdr7hivefnf75omqwg2jkee

Multiple attribute decision making with intuitionistic fuzzy information and uncertain attribute weights using minimization of regret

Yujun Luo, Guiwu Wei
2009 2009 4th IEEE Conference on Industrial Electronics and Applications  
Multiple attribute decision making problems with uncertain weights in intuitionistic fuzzy setting are investigated.  ...  Based on the technology for order preference by similarity to idea solution (TOPSIS) method and the score matrix converted from decision matrix given in the form of intuitionistic fuzzy number (IFN), some  ...  As a more suitable way to deal with vagueness than classical fuzzy set, IFS plays an important role in solving the complicated multiple attribute decision making (MADM) problems, especially in the circumstances  ... 
doi:10.1109/iciea.2009.5138897 fatcat:s65b6eeizfb6hcb3rwlxkclcja

Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games

Gabriele Farina, Christian Kroer, Tuomas Sandholm
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Regret minimization is a powerful tool for solving large-scale extensive-form games. State-of-the-art methods rely on minimizing regret locally at each decision point.  ...  Our generalization to convex compact sets and convex losses allows us to develop new algorithms for several problems: regularized sequential decision making, regularized Nash equilibria in zero-sum extensive-form  ...  We start with a brief review of regret minimization. Then, we introduce the domain on which we operate, sequential decision making.  ... 
doi:10.1609/aaai.v33i01.33011917 fatcat:qncl4dngprfrjatbw3njsf2urq

Page 54 of Journal of Risk and Insurance Vol. 27, Issue 4 [page]

1960 Journal of Risk and Insurance  
Minimizing the expected regret is the same as minimizing the expected loss in utility. Therefore, all that has been said regarding the decision-making rule in Case III is true here.  ...  Relaxation of Assumptions In the preceding paragraphs, several possible decision-making rules were dis- cussed, and each one may have been used at some time by a small group of insur- ance consumers or  ... 

Context-driven regret-based model of travel behavior under uncertainty: a latent class approach

Eleni Charoniti, Soora Rasouli, Harry J.P. Timmermans
2017 Transportation Research Procedia  
people face when making route choice decisions.  ...  Using route choice in an activity context as an example, we estimate a latent class random regret-minimization model, which takes into account the travel time and therefore arrival time uncertainty that  ...  Estimation results of the latent class regret-minimization model The regret minimization model, outlined in section 2, was estimated using the responses to the stated choice experiment.  ... 
doi:10.1016/j.trpro.2017.05.073 fatcat:2abp3c3ywbbl3mywayialbclra

Consequences of Regret Aversion 2: Additional Evidence for Effects of Feedback on Decision Making

Marcel Zeelenberg, Jane Beattie
1997 Organizational Behavior and Human Decision Processes  
In previous research, using the standard, context-free, gamble paradigm, we found that decision makers anticipate the regret they can experience as a result of post-decisional feedback on forgone outcomes  ...  We discuss the effects of anticipated and experienced regret on decision making under uncertainty.  ...  Conclusion People are motivated to avoid or minimize post-decisional regret.  ... 
doi:10.1006/obhd.1997.2730 fatcat:uipxox5ol5bahismda5rgphzoa

Regret Circuits: Composability of Regret Minimizers [article]

Gabriele Farina, Christian Kroer, Tuomas Sandholm
2019 arXiv   pre-print
In this paper we study the general composability of regret minimizers.  ...  Regret minimization is a powerful tool for solving large-scale problems; it was recently used in breakthrough results for large-scale extensive-form game solving.  ...  Regret circuit representing the construction of an (X ∩ Y, L)-regret minimizer using a (X , L)-regret minimizer.  ... 
arXiv:1811.02540v2 fatcat:awlsrr75bvfhzgzb46jaizd6hu

Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games [article]

Gabriele Farina, Christian Kroer, Tuomas Sandholm
2018 arXiv   pre-print
Regret minimization is a powerful tool for solving large-scale extensive-form games. State-of-the-art methods rely on minimizing regret locally at each decision point.  ...  Our generalization to convex compact sets and convex losses allows us to develop new algorithms for several problems: regularized sequential decision making, regularized Nash equilibria in extensive-form  ...  In this paper we consider the more general problem of how to minimize regret over a sequential decision-making (SDM) polytope, where we allow arbitrary compact convex subsets of simplexes at each decision  ... 
arXiv:1809.03075v1 fatcat:u6moiy2hwbcevacguqu6e66nby

A Comparative Study of Fuzzy Logic towards the Motivation and Anxiety on a Sportsman

Jon Arockiaraj J, Barathi E
2014 International Journal of Computing Algorithm  
The aim of this article is to deduce the relationship between anxiety and motivation of a sportsman using fuzzylogic. Sports contains physiological and social dimension.  ...  The quality of the playing is very much depending on both physiological and as well as psychological aspects of the player.  ...  Table1 Predicting The Mmr Of Hockey Players Decision making using minimization of regret was introduced by Savage and generalized by Yager by using Ordered weighted average(OWA) operator.Assume we have  ... 
doi:10.20894/ijcoa.101.003.003.008 fatcat:sk24by33lvh2rg57z2kxip2t7m

Robust Satisficing via Regret Minimization

Marcel Zeelenberg
2015 Journal of Marketing Behavior  
I propose that in everyday decision making, robust satisficing may occur via regret minimization.  ...  Schwartz (2015) argues that a rational decision-maker should not always strive for maximization.  ...  Anyhow, a number of decision rules have been described that can be used to make good decisions is these situations (see, e.g., Acker 1997; Yates 1990) .  ... 
doi:10.1561/107.00000010 fatcat:zifbbvg4dbej7ifbjllouacnha

Weighing the techniques for data optimization in a database [article]

Anagha Radhakrishnan
2022 arXiv   pre-print
On the other hand, ranking queries make use of specific scoring functions to rank tuples in a database.  ...  An experimental evaluation of datasets can provides us with information on the effectiveness of each of these methods.  ...  REGRET MINIMIZATION K-representative regret minimizing query (k-regret) is a useful operator for supporting multi-criteria decision-making.  ... 
arXiv:2203.09236v1 fatcat:fnscups23bgvvoi6flw7r3aiwm

The ecological rationality of decision criteria

Paolo Galeazzi, Alessandro Galeazzi
2020 Synthese  
Minimizing regret also finds some evolutionary justifications in our results, while maximin seems to be always disadvantaged by differential selection.  ...  for rational choice is analyzed through Monte Carlo simulations over various classes of decision problems.  ...  If material is not included in the article's Creative Commons licence and your intended use is not permitted  ... 
doi:10.1007/s11229-020-02785-y fatcat:tvw4l75zg5frpmmwb32a3bhaci

Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games [article]

Gabriele Farina, Tuomas Sandholm
2021 arXiv   pre-print
Most regret-minimization algorithms for tree-form sequential decision making, including CFR, require (i) an exact model of the player's decision nodes, observation nodes, and how they are linked, and (  ...  Regret minimization has proved to be a versatile tool for tree-form sequential decision making and extensive-form games.  ...  their valuable feedback while preparing our manuscript, and to Marc Lanctot and Vinicius Zambaldi for their help in tuning the hyperparameters and running experiments for the policy gradient algorithm of  ... 
arXiv:2103.04539v1 fatcat:3s5z2crajvamplbizn65dwn5ky
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