scholarly journals Toward Reverse Engineering to Economic Analysis: An Overview of Tools and Methodology

2021 ◽  
Author(s):  
Marisa Faggini ◽  
Bruna Bruno ◽  
Anna Parziale
Keyword(s):  
Complex System ◽  
Nonlinear Dynamics ◽  
Economic Analysis ◽  
Complex Systems ◽  
Reverse Engineering ◽  
Underlying Mechanism ◽  
Economic Data ◽  
Agent Based ◽  
Economic Agents ◽  
Advantages And Disadvantages

AbstractFollowing the reverse engineering (RE) approach to analyse an economic complex system is to infer how its underlying mechanism works. The main factors that condition the difficulty of RE are the number of variable components in the system and, most importantly, the interdependence of components on one another and nonlinear dynamics. All those aspects characterize the economic complex systems within which economic agents make their choices. Economic complex systems are adopted in RE science, and they could be used to understand, predict and model the dynamics of the complex systems that enable to define and to control the economic environment. With the RE approach, economic data could be used to peek into the internal workings of the economic complex system, providing information about its underling nonlinear dynamics. The idea of this paper arises from the aim to deepen the comprehension of this approach and to highlight the potential implementation of tools and methodologies based on it to treat economic complex systems. An overview of the literature about the RE is presented, by focusing on the definition and on the state of the art of the research, and then we consider two potential tools that could translate the methodological issues of RE by evidencing advantages and disadvantages for economic analysis: the recurrence analysis and the agent-based model (ABM).

scholarly journals Framework of Experimental Design and Data Mining in Multi-agent Simulation

2022 ◽  
pp. 1-7
Author(s):  
Fa Zhang ◽  
Shi-Hui Wu ◽  
Zhi-Hua Song
Keyword(s):  
Complex System ◽  
Data Mining ◽  
Experimental Design ◽  
Complex Systems ◽  
Key Factors ◽  
Agent Based ◽  
Meta Model ◽  
Reduction Methods ◽  
Multi Agent ◽  
Using Data

Multi-agent based simulation (MABS) is an important approach for studying complex systems. The Agent-based model often contains many parameters, these parameters are usually not independent, with differences in their range, and may be subjected to constraints. How to use MABS investigating complex systems effectively is still a challenge. The common tasks of MABS include: summarizing the macroscopic patterns of the system, identifying key factors, establishing a meta-model, and optimization. We proposed a framework of experimental design and data mining for MABS. In the framework, method of experimental design is used to generate experiment points in the parameter space, then generate simulation data, and finally using data mining techniques to analyze data. With this framework, we could explore and analyze complex system iteratively. Using central composite discrepancy (CCD) as measure of uniformity, we designed an algorithm of experimental design in which parameters could meet any constraints. We discussed the relationship between tasks of complex system simulation and data mining, such as using cluster analysis to classify the macro patterns of the system, and using CART, PCA, ICA and other dimensionality reduction methods to identify key factors, using linear regression, stepwise regression, SVM, neural network, etc. to build the meta-model of the system. This framework integrates MABS with experimental design and data mining to provide a reference for complex system exploration and analysis.

scholarly journals Challenges of Complexity in the 21st Century. An Interdisciplinary Introduction

2009 ◽  
Vol 17 (2) ◽  
pp. 219-236 ◽  
Author(s):  
Klaus Mainzer
Keyword(s):  
Nonlinear Dynamics ◽  
Complex Systems ◽  
Social Economic ◽  
Evolutionary Economics ◽  
Systems Science ◽  
Homo Oeconomicus ◽  
Economic Agents ◽  
Modern Engineering ◽  
Innovation Dynamics ◽  
Non Gaussian

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. Modern evolutionary economics can be modelled in the framework of complex systems and nonlinear dynamics. Historically, evolutionary economics was inspired by Schumpeterian concepts of business cycles and innovation dynamics. What are the laws of sociodynamics? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the complexity in firms, institutions and organizations? The world-wide crisis of financial markets and economies is a challenge for complexity research. Misleading concepts of linear thinking and mild randomness (e.g. Gaussian distributions of Brownian motion) must be overcome by new approaches of nonlinear mathematics (e.g. non-Gaussian distribution), modelling the wild randomness of turbulence at the stock markets. Systemic crises need systemic answers. Nevertheless, human cognitive capabilities are often overwhelmed by the complexity of nonlinear systems they are forced to manage. Traditional mathematical decision theory assumed perfect rationality of economic agents (homo oeconomicus). Herbert Simon, Nobel Prize laureate of economics and one of the leading pioneers of systems science and cognitive science, introduced the principle of bounded rationality. Therefore, we need new insights into the factual microeconomic behaviour of economic agents by methods of humanities, cognitive and social sciences, which are sometimes called ‘experimental economics’. Social and economic dynamics are interdisciplinary challenges of modern complexity research.

Comparative Study in the Barnyard

1975 ◽  
Vol 35 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Sylvia L. Thrupp
Keyword(s):  
Statistical Theory ◽  
Economic Analysis ◽  
Comparative Study ◽  
Social Institutions ◽  
Social Analysis ◽  
Economic Data ◽  
Recent Past ◽  
The Social ◽  
Fundamental Shift

For anyone on the green side of fifty who didn't start historical browsing in the playpen it may be quite hard to see the present appeal of statistical theory and method in perspective. To one lucky enough to have been a student abroad in the 1920's, it is merely one of the consequences of a fundamental shift, which was firming in that decade, in conceptions of the economic historian's job. Essentially the shift consisted in making the economy and the social institutions in which it is embedded analytically distinct. Voices from the Polanyite school still claim that this step was as wrong as Adam's eating of the apple. Milder critics complain only that some of us let economic analysis run away with the ball to the neglect of social analysis and of the interplay between the two. For workers on the recent past this is defensible, because the heavy fall-out of purely economic data clamors to be dealt with in its own terms. The preindustrialist, who has to dig harder for data, and seldom turns up such pure economic ore, is more inclined to think in terms of interplay.

scholarly journals Theoretical and Methodological Approaches to Ecological Changes, Social Behaviour and Human Intergroup Tolerance 300,000 to 30,000 BP

2021 ◽  
Vol 28 (1) ◽  
pp. 53-75 ◽  
Author(s):  
Penny Spikins ◽  
Jennifer C. French ◽  
Seren John-Wood ◽  
Calvin Dytham
Keyword(s):  
Social Behaviour ◽  
Environmental Variability ◽  
Raw Materials ◽  
Modern Human ◽  
Resource Exploitation ◽  
Agent Based ◽  
Advantages And Disadvantages ◽  
Ecological Changes ◽  
The Relationship ◽  
Social Behaviours

AbstractArchaeological evidence suggests that important shifts were taking place in the character of human social behaviours 300,000 to 30,000 years ago. New artefact types appear and are disseminated with greater frequency. Transfers of both raw materials and finished artefacts take place over increasing distances, implying larger scales of regional mobility and more frequent and friendlier interactions between different communities. Whilst these changes occur during a period of increasing environmental variability, the relationship between ecological changes and transformations in social behaviours is elusive. Here, we explore a possible theoretical approach and methodology for understanding how ecological contexts can influence selection pressures acting on intergroup social behaviours. We focus on the relative advantages and disadvantages of intergroup tolerance in different ecological contexts using agent-based modelling (ABM). We assess the relative costs and benefits of different ‘tolerance’ levels in between-group interactions on survival and resource exploitation in different environments. The results enable us to infer a potential relationship between ecological changes and proposed changes in between-group behavioural dynamics. We conclude that increasingly harsh environments may have driven changes in hormonal and emotional responses in humans leading to increasing intergroup tolerance, i.e. transformations in social behaviour associated with ‘self-domestication’. We argue that changes in intergroup tolerance is a more parsimonious explanation for the emergence of what has been seen as ‘modern human behaviour’ than changes in hard aspects of cognition or other factors such as cognitive adaptability or population size.

In-Between and Through: Architecture and Complexity

2005 ◽  
Vol 3 (3) ◽  
pp. 335-354 ◽  
Author(s):  
Clarissa Ribeiro Pereira de Almeida ◽  
Anja Pratschke ◽  
Renata La Rocca
Keyword(s):  
Complex System ◽  
Software Engineering ◽  
Complex Systems ◽  
Design Process ◽  
Three Dimensional ◽  
Self Organization ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Complex Thought ◽  
Basic Characteristics

This paper draws on current research on complexity and design process in architecture and offers a proposal for how architects might bring complex thought to bear on the understanding of design process as a complex system, to understand architecture as a way of organizing events, and of organizing interaction. Our intention is to explore the hypothesis that the basic characteristics of complex systems – emergence, nonlinearity, self-organization, hologramaticity, and so forth – can function as effective tools for conceptualization that can usefully extend the understanding of the way architects think and act throughout the design process. To illustrate the discussions, we show how architects might bring complex thought inside a transdisciplinary design process by using models such as software engineering diagrams, and three-dimensional modeling network environments such as media to integrate, connect and ‘trans–act’.

scholarly journals Use of the Multi-Agent Paradigm in Sustainable Tourism

2018 ◽  
Vol 7 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Martina Husáková
Keyword(s):  
Complex Systems ◽  
Sustainable Tourism ◽  
Multi Agent Systems ◽  
Economic Prosperity ◽  
Cultural Economic ◽  
Bottom Up ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
In Silico Models

Abstract Complex systems are characterised by a huge amount of components, which are highly linked with each other. Tourism is one of the examples of complex systems collecting various activities leading to the enrichment of travellers in the view of receiving new experiences and increasing economic prosperity of specific destinations. The complex systems can be investigated with various bottom-up and top-down approaches. The multi-agent-based modelling is the bottom-up approach that is focused on the representation of individual entities for the exploration of possible interactions among them and their effects on surrounding environments. These systems are able to integrate knowledge of socio-cultural, economic, physical, biological or environmental systems for in-silico models development, which can be used for experimentation with a system. The main aim of the presented text is to introduce links between tourism, complexity and to advocate usefulness of the multi-agent-based systems for the exploration of tourism and its sustainability. The evaluation of suitability of the multi-agent systems in tourism is based on the investigation of fundamental characteristics of these two systems and on the review of specific applications of the multi-agent systems in sustainable tourism.

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