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The aim of this paper is to build a computational model that presents the effects of social dynamics such as evolution on populations applying the theory of Hobbesian Social Contract, social learning and norm diffusion. The phenomenon we are studying is the so-called tragedy of the commons, in which individual agents, having open access to a resource unconstrained by common social structures, act according to their own self-interest, seeking to maximise their own profits. Developing the theoretical framework and agent-based model, we applied to our artificial environment the norm associated with altruism, which modifies agents' behaviour during the simulation, which in turn affects the distribution of wealth. Through the behavioural space, we show that under certain circumstances specified in the parameter, it is possible to obtain a social contract and, as a result, a state of equilibrium. We show that individuals who have obtained the norm are able to enter into a contract, resulting in a rising wealth of the population and a more equilibrium distribution, while if they do not, more inequalities emerge. However, our model is a simplification of Hobbes' theory, admittedly, our agents can spontaneously establish cooperation but there are no complex structures, such as psychological ones, or moral cognition. We believe that this is a skeletal description of the Hobbesian social contract, in which self-interested individuals without obligation to cooperate agree to abide by a norm and its benefits. Depending on how profitable cooperation is (due to the redistribution) and the number of altruistic agents, the community members work for the common good.
In: Annual review of political science, Band 17, S. 1-20
ISSN: 1545-1577
Agent-based models (ABMs) provide a methodology to explore systems of interacting, adaptive, diverse, spatially situated actors. Outcomes in ABMs can be equilibrium points, equilibrium distributions, cycles, randomness, or complex patterns; these outcomes are not directly determined by assumptions but instead emerge from the interactions of actors in the model. These behaviors may range from rational and payoff-maximizing strategies to rules that mimic heuristics identified by cognitive science. Agent-based techniques can be applied in isolation to create high-fidelity models and to explore new questions using simple constructions. They can also be used as a complement to deductive techniques. Overall, ABMs offer the potential to advance social sciences and to help us better understand our complex world. Adapted from the source document.
In: Annual review of political science, Band 17, Heft 1, S. 1-20
ISSN: 1545-1577
Agent-based models (ABMs) provide a methodology to explore systems of interacting, adaptive, diverse, spatially situated actors. Outcomes in ABMs can be equilibrium points, equilibrium distributions, cycles, randomness, or complex patterns; these outcomes are not directly determined by assumptions but instead emerge from the interactions of actors in the model. These behaviors may range from rational and payoff-maximizing strategies to rules that mimic heuristics identified by cognitive science. Agent-based techniques can be applied in isolation to create high-fidelity models and to explore new questions using simple constructions. They can also be used as a complement to deductive techniques. Overall, ABMs offer the potential to advance social sciences and to help us better understand our complex world.
In: Quantitative applications in the social sciences 153
In: Lecture Notes in Economics and Mathematical Systems 564
Aims to give a view of the scientific production in the fields of Agent-based Computational Economics, mainly in Market Finance and Game Theory. Based on communications given at AE'2005 (Lille, USTL, France), this book offers a panorama of advances in ACE, both theoretical and methodological that is of interest academics as well as practitioners
In: Lecture notes in economics and mathematical systems 564
Doutoramento em Economia ; A crise financeira de 2007/2008 desencadeou uma onda de críticas à teoria económica. Ataques baseados em quatro críticas principais: os economistas não terem previsto a maior crise desde a Grande Depressão; as autoridades deixarem formar bolhas sem controlo; o falhanço da supervisão bancária; e os modelos usados serem desfasados da realidade. No caso dos modelos, o alvo principal são os modelos DSGE (dinâmicos, estocásticos e de equilíbrio geral) e duas das suas hipóteses simplificadoras: o agente representativo e a racionalidade. As economias são realidades complexas, não-lineares e heterogéneas, e o recurso a métodos computacionais pode ser uma alternativa para ultrapassar as limitações dos modelos tradicionais. O objectivo desta tese é alargar a aplicação dos modelos de agentes em Macroeconomia com três exemplos distintos. O primeiro é um modelo de crescimento endógeno, de gerações sobrepostas, em que a decisão dos agentes sobre estudar é baseada na satisfação e na influência dos seus pares. É usado para testar os efeitos de longo prazo do paradoxo de Easterlin, que sugere que a satisfação e o rendimento não têm uma relação linear. Verifica-se que, no cenário de Easterlin, o crescimento é menor do que no cenário base onde os agentes atribuem igual importância ao rendimento absoluto e relativo. O segundo modelo visa avaliar o contágio dos defaults da dívida pública e a forma como as estratégias dos governos afetam o seu aparecimento e propagação. As simulações mostram que os países mais gastadores e com menor aversão ao risco tendem a entrar mais vezes em default e que políticas monetárias muito expansionistas podem originar fenómenos de risco moral. No terceiro modelo, estudamos o fenómeno da 'fuga de cérebros' e as consequências no crescimento económico. Concluímos que o efeito positivo do brain drain na acumulação de capital humano depende fortemente da probabilidade de emigrar. ; The 2007/2008 financial crisis triggered a wave of criticism of the economic theory. These attacks are based in four main critics: economists had not foreseen the biggest crisis since the Great Depression; authorities let bubbles form without control; weak banking supervision; and the models used in macroeconomic policy being out of touch with reality. In the particular case of the macroeconomic models, the target are the DSGE models (dynamic, stochastic and general equilibrium) and their two simplifying hypotheses: the representative agent and rationality. Economies are complex realities, with nonlinearities and heterogeneities, and computational economics can be an advantageous alternative to overcome the shortcomings of the traditional models. The aim of this thesis is to extend the application of agent-based models to macroeconomic topics in three distinct models. The first one is an endogenous growth model, in an overlapping generations environment, in which the agents' individual decision to study is based on the satisfaction of their peers. It is used to evaluate the long-term effects of the Easterlin paradox, which states that satisfaction and income have a non-linear relation. The second model is used to study sovereign default contagion in order to assess how different government strategies affect default and propagation across countries. Simulations showed that high spending and low risk aversion levels are associated to a high prevalence of default and that monetary stimulus can create moral hazard problems. In the third model, we study the brain drain phenomenon and its economic growth effects. We conclude that beneficial brain hypothesis depend heavily on emigration probability. ; info:eu-repo/semantics/publishedVersion
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In: Defence Technology, Band 18, Heft 7, S. 1219-1231
ISSN: 2214-9147
In: European Quarterly of Political Attitudes and Mentalities: EQPAM, Band 2, Heft 1, S. 1-26
ISSN: 2285-4916
This paper is about the theoretical implications of agent-based modeling exercises. Construction of
an agent-based model challenges a social scientist to formalize many concepts and relationships
that would have remained implicit or unrecognized. While formalizing these "unimportant"
assumptions can be a nuisance, it can also have substantial theoretical payoffs. In order to fill the
gaps of the model, the researcher is forced to confront the gaps in the theory that motivated the
model in the first place. Using examples drawn from several large political science simulation
models, the paper argues that frailty, defined as unpredictability in the behavior of agents, is often
required in order to bring closure to the modeling exercise. It is difficult (or impossible) to square
the dynamic or aggregate implications of the agent-based model with observations without placing
a substantial amount of emphasis on frailty. Hence, the component in behavior that we often treat
as "error" in empirical analysis is actually a vital part of the glue that makes the many different
moving parts of a social system interact in coherent ways. The example models were developed
with the Swarm simulation system (http://www.swarm.org) during the last decade.
Virtually all current major social and environmental challenges such as financial crises, migration, the erosion of democratic institutions, and the loss of biodiversity involve complex systems comprising decision-making, interacting, adaptive agents. To understand how such agent-based complex systems function and respond to change and disturbances, agent-based modeling (ABM) is increasingly recognized as the main way forward. Many motivating examples of agent-based models exist that are realistic enough to successfully support the management of complex systems, but these solutions are case-specific and contribute few general insights into the functioning of systems. General theory, though, is highly needed because we cannot model each system and question. Still, across disciplines, a critical mass of expertise has accumulated that could transform ABM into a more coherent and efficient approach to discover the functioning of complex social-economic-ecological systems. To this end, we need a cross-disciplinary discussion among researchers and a goal-oriented synthesis to identify the general principles and theories essential to improve our understanding and management of complex systems.
BASE
In: New economic windows
The primary goal of this book is to present the research findings and conclusions of physicists, economists, mathematicians and financial engineers working in the field of "Econophysics" who have undertaken agent-based modelling, comparison with empirical studies and related investigations. Most standard economic models assume the existence of the representative agent, who is "perfectly rational" and applies the utility maximization principle when taking action. One reason for this is the desire to keep models mathematically tractable: no tools are available to economists for solving non-linear models of heterogeneous adaptive agents without explicit optimization. In contrast, multi-agent models, which originated from statistical physics considerations, allow us to go beyond the prototype theories of traditional economics involving the representative agent. This book is based on the Econophys-Kolkata VII Workshop, at which many such modelling efforts were presented. In the book, leading researchers in their fields report on their latest work, consider recent developments and review the contemporary literature
Agent-based modelling in economics Lynne Hamill and Nigel Gilbert, Centre for Research in Social Simulation (CRESS), University of Surrey, UK New methods of economic modelling have been sought as a result of the global economic downturn in 2008. This unique book highlights the benefits of an agent-based modelling (ABM) approach. It demonstrates how ABM can easily handle complexity: heterogeneous people, households and firms interacting dynamically. Unlike traditional methods, ABM dus not require people or firms to optimise or economic systems to reach equilibrium. ABM offers a way to link micro foundations directly to the macro situation. Key features: -Introduces the concept of agent-based modelling and shows how it differs from existing approaches.-Provides a theoretical and methodological rationale for using ABM in economics, along with practical advice on how to design and create the models.-Each chapter starts with a short summary of the relevant economic theory and then shows how to apply ABM.-Explores both topics covered in basic economics textbooks and current important policy themes; unemployment, exchange rates, banking and environmental issues.-Describes the models in pseudocode, enabling the reader to develop programs in their chosen language.-Supported by a website featuring the NetLogo models described in the book. Agent-based Modelling in Economics provides students and researchers with the skills to design, implement, and analyze agent-based models. Third year undergraduate, master and doctoral students, faculty and professional economists will find this book an invaluable resource.