Results 331 to 340 of about 2,151,300 (377)

Monotonicity and robustness of majority rule

Economics Letters, 2010
Abstract I show that the majority rule is not “superior” to other rules if independence of irrelevant alternatives is replaced with monotonicity in the Dasgupta and Maskin (2008a) framework. In addition, I introduce a diversity requirement for preferences that restores the superiority of the majority rule in case of monotonicity.
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Monotone optimal decision rules and their computation

Journal of Optimization Theory and Applications, 1986
For a given objective functionw(x, a) onX × A, a maximizinga=δ(x) has to be determined for eachx in the totally ordered setX. We give conditions onw such that there is a monotone δ which can be computed recursively ifA is finite.
Harald Benzing, Michael Kolonko
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Monotonic Assignment Rules and Common Pricing

Mathematics of Operations Research, 2006
In this paper we study the production and pricing of a good by a single supplier (such as a monopolist or government) under some given optimality criterion—for example, profit maximization or social benefit maximization. In general, this may require discriminatory pricing.
James Bergin, Lin Zhou
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Minimal monotonic extensions of scoring rules

Social Choice and Welfare, 2005
Noting the existence of social choice problems over which no scoring rule is Maskin monotonic, we characterize minimal monotonic extensions of scoring rules. We show that the minimal monotonic extension of any scoring rule has a lower and upper bound, which can be expressed in terms of alternatives with scores exceeding a certain critical score.
Orhan Erdem, Orhan Erdem, M. Remzi Sanver   +2 more
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Splitting Rules for Monotone Fuzzy Decision Trees

2023
This paper considers the problem of building monotone fuzzy decision trees when the attributes and the labeling function are in the form of partitions (in Ruspini’s sense) of totally ordered labels. We define a fuzzy version of Shannon and Gini rank discrimination measures, based on a definition of fuzzy dominance, to be used in the splitting phase of ...
Marsala, Christophe, Petturiti, Davide
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Stable Risk Sharing and Its Monotonicity

, 2017
We consider a risk sharing problem in which agents pool their random costs together and seek an allocation rule to redistribute the risk back to each agent. The problem is put into a cooperative game framework and we focus on two salient properties of an
Xin Chen, Zhenyu Hu, Shuanglong Wang
semanticscholar   +1 more source

Learning of non-monotonic rules by simple perceptrons [PDF]

Journal of Physics A: Mathematical and General, 1998
In this paper, we study the generalization ability of a simple perceptron which learns an unrealizable Boolean function represented by a perceptron with a non-monotonic transfer function of reversed-wedge type. This type of non-monotonic perceptron is considered as a variant of multilayer perceptron and is parametrized by a single `wedge' parameter a ...
Yoshiyuki Kabashima, Jun-ichi Inoue
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Inductive discovery of laws using monotonic rules

Engineering Applications of Artificial Intelligence, 2012
We are considering knowledge discovery from data describing a piece of real or abstract world. The patterns being induced put in evidence some laws hidden in the data. The most natural representation of patterns-laws is by ''if..., then...'' decision rules relating some conditions with some decisions.
Blaszczynski J, GRECO, Salvatore, Slowinski R.   +2 more
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On the Existence of Monotone Optimal Decision Rules

1984
Consider the following general decision poblem: find a decision rule δ such that $$w\left( {x,\delta \left( x \right)} \right) = \max _{a \in A} w\left( {x,a} \right)$$ (1) for all samples x ∈ X, where w is a given target function. The necessary effort for finding such an optimal δ is reduced if δ is known to be contained in a particular set ...
Harald Benzing, Michael Kolonko
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Monotone Decision Rules for the Two-Armed Bandit [PDF]

, 1984
Consider the following problem in sequential design: Two Bernoulli experiments called arm 1 and arm 2 are given with unknown success probabilities. We consider them as random variables with a joint prior distribution μ not concentrated on the boundary of [0, 1]2. The aim is to maximize the expected number of successes in N trials by choosing one of the
Harald Benzing, Michael Kolonko
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