An Overview of Social Simulation Research in Brazil

Sichman, Jaime Simão; Costa, Antônio Carlos da Rocha; Adamatti, Diana Francisca; Dimuro, Graçaliz Pereira; Buarque, Fernando; Bommel, Pierre

doi:10.1109/bwss.2012.31

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Then, we are aiming at applications in the context of hybrid BDI-fuzzy [35] 5 agent models, commonly used in social simulation [37][38][39][40], where the evaluation of social values and exchanges are of a qualitative and subjective nature [41][42][43]. We noticed that overlap and grouping functions can be used for dealing with indifference and incomparability when reasoning on the agent's fuzzy belief base, where a kind of weak preference relation may be defined.…”

Section: Resultsmentioning

confidence: 99%

On additive generators of overlap functions

Dimuro

Bedregal

Bustince

et al. 2016

Fuzzy Sets and Systems

136

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In this paper we introduce the notion of additive generator pair for overlap functions. We also study how some of the properties that can be demanded to an overlap function can be expressed in terms of its generator pair. In particular, given a continuous and positive t-norm T , we analyze the overlap functions which are obtained by the distortion of T by a pseudo-automorphism, showing that the additive generator pair of such overlap function may be given in terms of the considered pseudo-automorphism and the additive generator of T . Finally, we also consider the influence of the migrativity, homogeneity and idempotency properties for the overlap functions obtained by such distortion in terms of their respective additive generator pairs.

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Section: Resultsmentioning

confidence: 99%

On additive generators of overlap functions

Dimuro

Bedregal

Bustince

et al. 2016

Fuzzy Sets and Systems

136

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“…In problems of decision making in an environment with uncertainty, the decision maker must estimate the probabilities of different actions, which may lead to different outcomes. However, sometimes these probabilities are difficult to estimate precisely, such as problems in agent-based social simulation [1,12,14], which often have linguistic variables to define some parameters of the agents involved in the modeling [2,11,15] under vagueness, ambiguity and uncertainty.…”

Section: Introductionmentioning

confidence: 99%

An approach to interval fuzzy probabilities

Asmus¹,

Bedregal²,

Dimuro³

2015

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Fuzzy sets an logic have been largely applied used to the treatment of the uncertainty, vagueness and ambiguity found in the modeling of real problems. However, there may exist also the case when there is uncertainty related to the membership functions to be used in the modeling of fuzzy sets and fuzzy numbers, as there are many ways to define the shape of this kind of number. Thus, one can use, for example, the theory of interval fuzzy sets to address this uncertainty, considering different modeling of fuzzy numbers into a single interval fuzzy number. In this paper, we use interval fuzzy numbers to represent probabilities that are difficult to be estimated and where the modeling of fuzzy numbers is not trivial. To elaborate the calculation of probabilities, it will be introduced an approach based on one used by Buckley and Eslami, where the probabilities respect an arithmetic restriction. We discuss several properties of the proposed approach.

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“…However, sometimes these probabilities are difficult to estimate precisely, such as problems in agent-based social simulation [1,2,3], which often have linguistic variables to define some parameters of the agents involved in the modeling [4,5,6] under vagueness, ambiguity and uncertainty.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Interval Fuzzy Probabilities

Asmus

Dimuro

Bedregal

2015

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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Fuzzy sets and logic have been largely used for the treatment of the uncertainty, vagueness and ambiguity found in the modeling of real problems. However, there may exist also the case when there is uncertainty related to the membership functions to be used in the modeling of fuzzy sets and fuzzy numbers, as there are many ways to define the shape of this kind of number. Thus, one can use, for example, the theory of interval fuzzy sets to address this uncertainty, considering different modelings of fuzzy numbers into a single interval fuzzy number. In this paper, we use interval fuzzy numbers to represent probabilities that are difficult to be estimated and where the modeling of fuzzy numbers is not trivial. To elaborate the calculation of interval fuzzy probabilities, we introduce an approach based on the one used by Buckley and Eslami for fuzzy probabilities, where the probabilities respect an arithmetic restriction. We discuss several properties of the proposed approach.

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An Overview of Social Simulation Research in Brazil

Cited by 3 publications

References 7 publications

On additive generators of overlap functions

On additive generators of overlap functions

An approach to interval fuzzy probabilities

An Approach to Interval Fuzzy Probabilities

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