George Mengov

George Mengov
Sofia University "St. Kliment Ohridski" · Faculty of Economics and Business Administration

Ph.D., Professor

About

39
Publications
10,191
Reads
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77
Citations
Introduction
George Mengov currently works at the Faculty of Economics and Business Administration, Sofia University St. Kliment Ohridski. George does research in Sociocybernetics. His current project is 'Decision Science.'
Additional affiliations
June 1996 - October 2000
Technical University of Sofia
Position
  • PhD Student

Publications

Publications (39)
Article
Full-text available
Economic forecasting is always difficult and in turbulent periods becomes nearly impossible: Time-series are short and nonstationary while theoretical underpinning is limited. The brain, however, has mechanisms to deal with that kind of challenges, and neuroscience has uncovered some of them. Here we show how a neural circuit model for emotion gene...
Conference Paper
Full-text available
Findings from laboratory studies with human participants often carry over to the real world. Here we analyze data from an economic experiment and show that introducing relevant expert information makes a lab market more chaotic, while connecting people via a virtual social network reduces chaos and increases self-organization. The latter may be of...
Conference Paper
Full-text available
Today's business and macroeconomic management needs precise forecasting of the near future with only a handful of observations, yet most econometric techniques demand dozens of historical records. Here we outline the design of an intelligent system built upon implicit knowledge from computational neu-roscience. Its main element is the gated dipole,...
Article
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Представен е отзив за книгата на Николай Рачев „Рационалност в културен контекст“ .
Article
Full-text available
Collective behaviour sums up the emotional and rational actions of many individuals. In the financial markets, the economic agents’ aggregate activity leads to price fluctuations driven by hope and fear, optimism and pessimism. While the market mood mechanism is unknown, a number of hypotheses exist including the suggestion that the mind’s complex...
Article
Full-text available
To understand how the brain gives rise to emotional human behaviour, modern neuroscience extensively uses computer modelling. The differential equation for long-term memory (LTM) is an important element of a variety of cognitive-emotional models, including the Grossberg-Schmajuk recurrent gated dipole. Usually, such models are composed of coupled o...
Conference Paper
Full-text available
How relevant economic information affects the agents’ business strategies is generally not well understood. In particular, macroeconomic data about current production and near-future forecasts are known to impact the decision makers’ thinking, but the evidence about how exactly this happens has been contradictory. A variety of theoretical explanati...
Conference Paper
Full-text available
Information technology made our lives unthinkable without using virtual social networks on daily basis. These networks not only gave us new opportunities to satisfy our social needs, but increased immensely the efficiency of various activities we carry out in collaboration with others. In this paper we present results from an economic experiment, c...
Article
Full-text available
Young people’s behaviour in virtual social networks is studied mainly with respect to their personal characteristics and how these change, or w.r.t. the network’s aggregate properties. The latter kind of study is especially popular when the object of discussion is goods or services, or experiences from holidays, parties, and other similar activitie...
Article
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An economic decision is important not only through its direct consequences – its objective utility – but also through the individual’s perceptions of its outcome. Today, economic decision-making is investigated with interdisciplinary methods, rooted in psychology, economics, mathematics, and computer science. Here we present an experiment in econom...
Article
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Currently, many methods for data analysis in the social sciences resort to applied statistics and even simpler extrapolation techniques. While such a toolbox provides a satisfactory base for conclusions and predictions, this state of affairs is hardly inspiring. Here, a knowledge transfer is advocated, whereby achievements of mathematical and compu...
Book
Full-text available
This book offers a new perspective on human decision-making by comparing the established methods in decision science with innovative modelling at the level of neurons and neural interactions. The book presents a new generation of computer models, which can predict with astonishing accuracy individual economic choices when people make them by quick...
Article
As we saw in the previous chapter, the link between income and wellbeing is complicated because they correlate only until the basic human needs are satisfied. Modern economic psychology has discovered that beyond that level, money changes its psychological function and becomes means for participation in social relationships, as well as for managing...
Article
In the preceding chapters, we covered two major approaches to decision analysis—the axiomatic, associated mainly with expected utility theory, and the psychological. Here I outline a third approach, which is the neurobiological modelling of the decision maker. It differs greatly from the former two as it employs an entirely new set of concepts , po...
Article
Many theorists of economic rationality formulated insightful postulates with a lot of common sense, yet human decision-making proved a hard nut to crack. Even the mildest of all principles, weak stochastic transitivity, was—as we saw—proven to be systematically violated. The agents seem to be in so much contradiction with their own preferences, tha...
Article
Decades ago, Grossberg’s cooperative-competitive models described equally well neurons, competing locally while exhibiting globally coordinated behavior, and production companies in a class of stable competitive markets. Recently, Apolloni posited that the social network is a fractal extension of the brain network. However, little has yet been done...
Article
As we saw in the preceding chapter, mathematical and computational neuroscience can successfully bridge the gap between decision science and the psychology of cognitive-emotional interactions. However, the limits within which neural models can explain empirical data from real economic choices remain virtually unknown. In this chapter, I present a s...
Article
Imagine that your job is to analyze data for your organization, which could be of any kind. Whether it is business data related to sales, revenue, market share, media coverage, production lines, agriculture, human resources, headcount, training, healthcare or something very different, you must understand what it is telling you and anticipate what t...
Article
In the year 1731, Daniel Bernoulli , a Dutchman educated at the University of Basel, delivered a lecture at a meeting of the St Petersburg Academy of Sciences in Russia, later published as a memoir in the Academy Proceedings. Dealing with a seemingly minor and specific problem, in that work he did no less than lay the foundations of what would beco...
Article
Many theorists of economic rationality formulated insightful postulates with a lot of common sense, yet human decision-making proved a hard nut to crack. Even the mildest of all principles, weak stochastic transitivity, was—as we saw—proven to be systematically violated. The agents seem to be in so much contradiction with their own preferences, tha...
Article
Full-text available
Decision making is an interdisciplinary field, which is explored with methods spanning from economic experiments to brain scanning. Its dominant paradigms such as utility theory, prospect theory, and the modern dual-process theories all resort to formal algebraic models or non-mathematical postulates, and remain purely phenomenological. An approach...
Article
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Article
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Using neuroscientific methods to study human decision-making is a new and exciting research area. Today it is dominated by observational approaches driven by the fMRI and other brain-imaging technologies, but it already links empirical data with concepts and findings from established paradigms such as utility theory and prospect theory. Developed i...
Article
Full-text available
Forecasting economic behaviour is an important problem with practical implications for a number of scientific disciplines, including microeconomics, macroeconomics, marketing and economic psychology. The ability to predict the economic agent's choice is a coveted goal for both social scientists and market practitioners. In our time, such studies ar...
Article
Full-text available
We propose a novel way to define a utility function which is based on the differential equations of Affective Balance Theory. Introduced in 1987 that theory is more general than the Nobel Prize winning Prospect Theory, but remained poorly understood by the decision-making community due to its bottom-up approach to choice behaviour involving biophys...
Article
This paper presents an experiment, which builds a bridge over the gap between neuroscience and the analysis of economic behaviour. We apply the mathematical theory of Pavlovian conditioning, known as Recurrent Associative Gated Dipole (READ), to analyse consumer choices in a computer-based experiment. Supplier reputations, consumer satisfaction, an...
Article
This work continues a series of papers about a neural network that incorporates adaptive resonance theory (ART) as a system of ordinary differential equations. The original, exact ART, requires huge computational resources even for small-scale tasks. However, for technological applications it is necessary to devise more efficient computing algorith...
Article
We address the need to develop efficient algorithms for numerical simulation of models, based in part or entirely on adaptive resonance theory. We introduce modifications that speed up the computation of the gated dipole field (GDF) in the Exact ART neural network. The speed increase of our solution amounts to at least an order of magnitude for fie...
Article
This paper is based on the idea that humans acquire knowledge not by learning information, but by remembering their own impressions of the new information. We analyze the performance of a neural network, which implements adaptive resonance theory (ART) as a system of ordinary differential equations. That network is Exact ART. We identify conditions...
Article
We outline an approach for solving numerically large-scale systems of ordinary differential equations using a Generalized Net (GN), and present an example from neural modelling. We discuss the transfer of signals between two neural cells via a synapse with chemical transmitters, modelled by a system of three coupled ordinary differential equations....
Article
In this paper we introduce a neural networks based approach to analyzing empirical data and models from work and organizational psychology (WOP), and suggest possible implications for the practice of managers and business consultants. With this method it becomes possible to have quantitative answers to a bunch of questions like: What are the charac...

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