138,809 research outputs found

    Modeling the Evolution of Companies using Intelligent Software Agents Architecture

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    The paper presents the concept of multi agent system that models the evolution of a company. The opportunity of such an approach and the limits of mathematical modeling are presented. The main players on the market are modeled as cognitive, adaptive, heterogeneous agents and evolve in a dynamic environment. The purpose is to use the model of operational agent that has these characteristics. This model is based on using an ATN (Augmented Transition Network) to adapt the behavior of its agent to the changes it detects in its environment. Each agent has an inference mechanism for the first order reasoning. The agents communicate between them through messages and will be implemented in a non synchronized object environment.multiagent system, economic model, discret events

    Learning the optimal buffer-stock consumption rule of Carroll

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    This article questions the rather pessimistic conclusions of Allen et Carroll (2001) about the ability of consumer to learn the optimal buffer-stock based consumption rule. To this aim, we develop an agent based model where alternative learning schemes can be compared in terms of the consumption behaviour that they yield. We show that neither purely adaptive learning, nor social learning based on imitation can ensure satisfactory consumption behaviours. By contrast, if the agents can form adaptive expectations, based on an evolving individual mental model, their behaviour becomes much more interesting in terms of its regularity, and its ability to improve performance (which is as a clear manifestation of learning). Our results indicate that assumptions on bounded rationality, and on adaptive expectations are perfectly compatible with sound and realistic economic behaviour, which, in some cases, can even converge to the optimal solution. This framework may therefore be used to develop macroeconomic models with adaptive dynamics.Consumption decisions; Learning; Expectations; Adaptive behaviour, Computational economics

    Learning the optimal buffer-stock consumption rule of Carroll

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    This article questions the rather pessimistic conclusions of Allen et Carroll (2001) about the ability of consumer to learn the optimal buffer-stock based consumption rule. To this aim, we develop an agent based model where alternative learning schemes can be compared in terms of the consumption behaviour that they yield. We show that neither purely adaptive learning, nor social learning based on imitation can ensure satisfactory consumption behaviours. By contrast, if the agents can form adaptive expectations, based on an evolving individual mental model, their behaviour becomes much more interesting in terms of its regularity, and its ability to improve performance (which is as a clear manifestation of learning). Our results indicate that assumptions on bounded rationality, and on adaptive expectations are perfectly compatible with sound and realistic economic behaviour, which, in some cases, can even converge to the optimal solution. This framework may therefore be used to develop macroeconomic models with adaptive dynamics.Consumption decisions; Learning; Expectations; Adaptive behaviour; Computational economics

    Human Development Dynamics: An Agent Based Simulation of Macro Social Systems and Individual Heterogeneous Evolutionary Games

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    Purpose: In the context of modernization and development, a complex adaptive systems framework can help address the coupling of macro social constraint and opportunity with individual agency. Combining system dynamics and agent based modeling, we formalize a simulation approach of the Human Development (HD) perspective to explore the interactive effects of economics, culture, society and politics across multiple human scales. Methods: Based on a system of asymmetric, coupled nonlinear equations, we first capture the core qualitative logic of HD theory, empirically validated from World Values Survey (WVS) data. Using a simple evolutionary game approach, second we fuse endogenously derived individual socio-economic attribute changes with Prisoner’s Dilemma in an agent based model of the interactive political-cultural effects of heterogeneous, spatial intra-societal economic transactions. We then explore a new human development dynamics (HDD) model behavior via quasiglobal simulation methods to identify paths and pitfalls towards economic development, cultural plasticity, social and political change behavior. Results: Our preliminary results suggest strong nonlinear path dependence and complexity in three areas: adaptive development processes, co-evolutionary societal transactions and near equilibrium development trajectories, with significant implications for anticipating and managing positive development outcomes. Strong local epistatic interactions characterized by adaptive co-evolution, shape higher order global conditions and ultimately societal outcomes. Conclusions: Techno-social simulations such as this can provide scholars and policymakers alike insights into the nonlinear, complex adaptive effects of societal co-evolution. We believe complex adaptive or evolutionary systems approaches are necessary to understand both near and potentially catastrophic, far-from-equilibrium behavior and societal outcomes across all human scales of modernization

    Efficacy of landfill tax and subsidy policies for the emergence of industrial symbiosis networks: An agent-based simulation study

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    Despite the theoretical value of industrial symbiosis (IS), this approach appears to be underdeveloped in terms of practical applications. Different attempts to stimulate IS in practice are noticed, one of them consisting in the application of adequate policy measures. This paper explores the efficacy of two specific policies (landfill tax and economic subsidy for IS exchanges) in supporting the emergence of self-organized industrial symbiosis networks (ISNs). We frame the ISNs as complex adaptive systems and we design an agent-based model to simulate their emergence. We use a real case study and, by means of the simulation model, we assess how the two policy measures are able to enhance the formation of spontaneous IS relationships, thereby forcing the emergence of the ISN. Results show that both policy measures have a positive effect in all scenarios considered, but the extent is strictly dependent on the environmental conditions in which IS relationships occur. The economic implications for the government are finally discussed

    Human Development Dynamics: an Agent Based Simulation of Macro Social Systems and Individual Heterogeneous Evolutionary Games

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    This is the final version of the article. Available from Springer via the DOI in this record.Purpose In the context of modernization and development, a complex adaptive systems framework can help address the coupling of macro social constraint and opportunity with individual agency. Combining system dynamics and agent based modeling, we formalize a simulation approach of the Human Development (HD) perspective to explore the interactive effects of economics, culture, society and politics across multiple human scales. Methods Based on a system of asymmetric, coupled nonlinear equations, we first capture the core qualitative logic of HD theory, empirically validated from World Values Survey (WVS) data. Using a simple evolutionary game approach, second we fuse endogenously derived individual socio-economic attribute changes with Prisoner’s Dilemma in an agent based model of the interactive political-cultural effects of heterogeneous, spatial intra-societal economic transactions. We then explore a new human development dynamics (HDD) model behavior via quasi-global simulation methods to identify paths and pitfalls towards economic development, cultural plasticity, social and political change behavior. Results Our preliminary results suggest strong nonlinear path dependence and complexity in three areas: adaptive development processes, co-evolutionary societal transactions and near equilibrium development trajectories, with significant implications for anticipating and managing positive development outcomes. Strong local epistatic interactions characterized by adaptive co-evolution, shape higher order global conditions and ultimately societal outcomes. Conclusions Techno-social simulations such as this can provide scholars and policymakers alike insights into the nonlinear, complex adaptive effects of societal co-evolution. We believe complex adaptive or evolutionary systems approaches are necessary to understand both near and potentially catastrophic, far-from-equilibrium behavior and societal outcomes across all human scales of modernization

    What if Hayek goes shopping in the bazaar?

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    The paper presents a comparative analysis of the peculiar institutional features of two retail markets: the middle eastern Bazaar and the western Mall (shopping center). We study the informational functions and performance of the different market institutions using an Agent Based Computational Economics (ACE) model under the assumption of behavioral learning by agents. Sellers decide which price setting strategy to adopt whereas buyers form their price beliefs exploring the market and decide which price to accept. The agents learn how to adapt and behave within the specific institutional framework to carry out their economic transactions, but market institutions, as mechanisms to coordinate information of market participants are expected to affect the price dynamics. The main area of interest concerns the question of whether the economic argument on the presumed underperformance of bazaar institutions respect to more competitive markets holds true or it is necessary a reassessment on it.Agent's beliefs; learning; adaptive behavior; market institutions; price dynamics

    Application of an Adaptive Step-Size Algorithm in Models of Hyperinflation

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    An adaptive step-size algorithm [Kushner and Yin, Stochastic Approximation and Recursive Algorithms and Applications, 2nd ed., New York: Springer-Verlag (2003)] is used to model time-varying learning, and its performance is illustrated in the environment of Marcet and Nicolini [American Economic Review 93 (2003), 1476–1498]. The resulting model gives qualitatively similar results to those of Marcet and Nicolini, and performs quantitatively somewhat better, based on the criterion of mean squared error. The model generates increasing gain during hyperinflations and decreasing gain after hyperinflations end, which matches findings in the data. An agent using this model behaves cautiously when faced with sudden changes in policy, and is able to recognize a regime change after acquiring sufficient information

    Evolution of Market Heuristics

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    The time evolution of aggregate economic variables, such as stock prices, is affected by market expectations of individual investors. Neo-classical economic theory assumes that individuals form expectations rationally, thus enforcing prices to track economic fundamentals and leading to an efficient allocation of resources. However, laboratory experiments with human subjects have shown that individuals do not behave fully rational but instead follow simple heuristics. In laboratory markets prices may show persistent deviations from fundamentals similar to the large swings observed in real stock prices. Here we show that evolutionary selection among simple forecasting heuristics can explain coordination of individual behavior leading to three different aggregate outcomes observed in recent laboratory market forecasting experiments: slow monotonic price convergence, oscillatory dampened price fluctuations and persistent price oscillations. In our model forecasting strategies are selected every period from a small population of plausible heuristics, such as adaptive expectations and trend following rules. Individuals adapt their strategies over time, based on the relative forecasting performance of the heuristics. As a result, the evolutionary switching mechanism exhibits path dependence and matches individual forecasting behavior as well as aggregate market outcomes in the experiments. Our results are in line with recent work on agent-based models of interaction and contribute to a behavioral explanation of universal features of financial markets.
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