Subjective modelling of supply and demand—the minimum of Fisher information solution

Physica A: Statistical Mechanics and its Applications

2014

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There is a common belief that humans and many animals follow transitive inference (choosing A over C on the basis of knowing that A is better than B and B is better than C). Transitivity seems to be the essence of rational choice. We present a theoretical model of a repeated game in which the players make a choice between three goods (e.g. food). The rules of the game refer to the simple procedure of fair division among two players, known as the "I cut, you choose" mechanism which has been widely discussed in the literature. In this game one of the players has to make intransitive choices in order to achieve the optimal result (for him/her and his/her co-player). The point is that an intransitive choice can be rational. Previously, an increase in the significance of intransitive strategies was achieved by referring to models of quantum games. We show that relevant intransitive strategies also appear in the classic description of decision algorithms.

Section: Resultsmentioning

confidence: 99%

When I cut, you choose method implies intransitivity

Physica A: Statistical Mechanics and its Applications

2014

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“…a maximum at the fixed point. Theorem 1 also has other interesting applications [5][6][7][8][9]. What is characteristic of the method we have presented is that when calculating the function of information processing intensity (both on the left and on the right), only those values which meet the condition specified by the cut-off parameter are used.…”

Section: Resultsmentioning

confidence: 99%

Parameter estimation by fixed point of function of information processing intensity

Jankowski

Physica A: Statistical Mechanics and its Applications

2014

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We present a new method of estimating the dispersion of a distribution which is based on the surprising property of a function that measures information processing intensity. It turns out that this function has a maximum at its fixed point. We use a fixed-point equation to estimate the parameter of the distribution that is of interest to us. We illustrate the estimation method by using the example of an exponential distribution. The codes of programs that calculate the experimental values of the information processing intensity are presented.

“…thus, inserting Eq. (70) into (71), we obtain: 9 Let us notice that from Eq. (71) it follows that A is the unbiased estimator of the expectation value A of the level of productivity, i.e., A = A.…”

Section: The Solution Of the Generating Equationmentioning

confidence: 99%

“…Below, its modified [6,7] version, which abandons the previous, arbitrary metrical form is presented and the solution to entailed equations of the fully analytical formulation of the information principles problem [6] is given. The approach is based on the maximum-likelihood estimation (MLE) and the Fisher information, both the observed and expected ones, defined as the expectation value of the observed information widely used in information geometry [8] and statistics [4,7,9,6]. A similar approach was previously used to analyse the problem of subjectivity in supply-demand related issues [10,9].…”

Section: Introductionmentioning

confidence: 99%

“…The approach is based on the maximum-likelihood estimation (MLE) and the Fisher information, both the observed and expected ones, defined as the expectation value of the observed information widely used in information geometry [8] and statistics [4,7,9,6]. A similar approach was previously used to analyse the problem of subjectivity in supply-demand related issues [10,9]. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Generalization of the Aoki–Yoshikawa sectoral productivity model based on extreme physical information principle

Bednarek

Physica A: Statistical Mechanics and its Applications

et al. 2015

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This paper presents a continuous variable generalization of the Aoki-Yoshikawa sectoral productivity model. Information theoretical methods from the Frieden-Soffer extreme physical information statistical estimation methodology were used to construct exact solutions. Both approaches coincide in first order approximation. The approach proposed here can be successfully applied in other fields of research.✩ Highlights: Assumptions of original Aoki-Yoshikawa sectoral productivity model (AYM) are given. Information channel capacity for the AYM in the extremal physical information (EPI) method is constructed. Analytical observed structural principle and variational one are found. Generating equation for AYM and probability distribution for AYM are found. Results of the original AYM and of the EPI method approach to AYM are compared.