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Articles de revues sur le sujet « Heterogeneous Agents Models »

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Auteur : Grafiati

Publié le 10 mars 2023

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1

Gatti, Domenico Delli, Corrado Di Guilmi, Mauro Gallegati et Simone Landini. « Reconstructing Aggregate Dynamics in Heterogeneous Agents Models ». Revue de l'OFCE 124, n^o 5 (2012) : 117. http://dx.doi.org/10.3917/reof.124.0117.

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2

Borissov, Kirill Yu, et Mikhail A. Pakhnin. « Social Welfare in Growth Models with Heterogeneous Agents ». St Petersburg University Journal of Economic Studies 35, n^o 2 (2019) : 173–96. http://dx.doi.org/10.21638/spbu05.2019.201.

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3

Boháček, Radim, et Michal Kejak. « Optimal government policies in models with heterogeneous agents ». Journal of Economic Theory 176 (juillet 2018) : 834–58. http://dx.doi.org/10.1016/j.jet.2018.05.008.

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4

Thiem, Thomas N., Felix P. Kemeth, Tom Bertalan, Carlo R. Laing et Ioannis G. Kevrekidis. « Global and local reduced models for interacting, heterogeneous agents ». Chaos : An Interdisciplinary Journal of Nonlinear Science 31, n^o 7 (juillet 2021) : 073139. http://dx.doi.org/10.1063/5.0055840.

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XU, YINGYING, ZHIXIN LIU et XING ZHANG. « HETEROGENEOUS OR HOMOGENEOUS INFLATION EXPECTATION FORMATION MODELS : A CASE STUDY OF CHINESE HOUSEHOLDS AND FINANCIAL PARTICIPANTS ». Singapore Economic Review 62, n^o 04 (septembre 2017) : 859–74. http://dx.doi.org/10.1142/s0217590817400306.

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This paper attempts to identify whether the inflation expectation formation models adopted by Chinese agents are heterogeneous or homogeneous. A Gaussian mixture model is developed assuming that agents form inflation expectations by selecting a model from alternatives. Analysis results reveal that only adaptive expectation (AE) model is significant, indicating that both households and financial participants are fairly homogeneous in selecting inflation expectation formation models. Therefore, the mechanism of heterogeneous models is inoperative in explaining the heterogeneous inflation expectations in China, and the AE is the main driver of Chinese agents’ perceptions about cost.

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Bertin, Eric. « Emergence of Simple Characteristics for Heterogeneous Complex Social Agents ». Symmetry 12, n^o 8 (2 août 2020) : 1281. http://dx.doi.org/10.3390/sym12081281.

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Models of interacting social agents often represent agents as very simple entities with a small number of degrees of freedom, as exemplified by binary opinion models for instance. Understanding how such simple individual characteristics may emerge from potentially much more complex agents is thus a natural question. It has been proposed recently in [E. Bertin, P. Jensen, C. R. Phys. 20, 329 (2019)] that some types of interactions among agents with many internal degrees of freedom may lead to a ‘simplification’ of agents, which are then effectively described by a small number of internal degrees of freedom. Here, we generalize the model to account for agent intrinsic heterogeneity. We find two different simplification regimes, one dominated by interactions, where agents become simple and identical as in the homogeneous model, and one where agents remain strongly heterogeneous although effectively with simple characteristics.

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Motta, Giorgio, et Patrizio Tirelli. « MONEY TARGETING, HETEROGENEOUS AGENTS, AND DYNAMIC INSTABILITY ». Macroeconomic Dynamics 19, n^o 2 (7 janvier 2014) : 288–310. http://dx.doi.org/10.1017/s1365100513000394.

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The limited asset-market participation hypothesis has triggered a debate on DSGE models' determinacy when the central bank implements a standard Taylor rule. We reconsider the issue here in the context of an exogenous money supply rule, documenting the role of nominal and real frictions in determining these results. A general conclusion is that frictions matter for stability insofar as they redistribute income between Ricardian and non-Ricardian households when shocks hit the economy. Finally, we extend the model to allow for the possibility that consumers who do not participate in the market for interest-bearing securities hold money. In this case, endogenous monetary transfers between the two groups make it possible to smooth consumption differences, and the model is determinate, provided that the non-negativity constraint on individual money holdings is satisfied.

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Den Haan, Wouter J., Kenneth L. Judd et Michel Juillard. « Computational suite of models with heterogeneous agents II : Multi-country real business cycle models ». Journal of Economic Dynamics and Control 35, n^o 2 (février 2011) : 175–77. http://dx.doi.org/10.1016/j.jedc.2010.09.010.

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M. Beaumont, P., A. J. Culham et A. N. Kercheval. « Asset Market Dynamics in Equilibrium Models with Heterogeneous Agents : Analytical Results ». Advances in Economics and Business 1, n^o 2 (septembre 2013) : 49–56. http://dx.doi.org/10.13189/aeb.2013.010202.

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Donaghy, Kieran P. « Models of travel demand with endogenous preference change and heterogeneous agents ». Journal of Geographical Systems 13, n^o 1 (11 septembre 2010) : 17–30. http://dx.doi.org/10.1007/s10109-010-0129-1.

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11

Di Guilmi, C., M. Gallegati, S. Landini et J. E. Stiglitz. « An analytical solution for network models with heterogeneous and interacting agents ». Journal of Economic Behavior & ; Organization 171 (mars 2020) : 189–220. http://dx.doi.org/10.1016/j.jebo.2020.01.017.

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12

Dräger, Lena. « RECURSIVE INATTENTIVENESS WITH HETEROGENEOUS EXPECTATIONS ». Macroeconomic Dynamics 20, n^o 4 (9 octobre 2015) : 1073–100. http://dx.doi.org/10.1017/s1365100514000741.

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We model agents' endogenous updating of information sets over time under changing macroeconomic conditions. Building on sticky information models, the degree of inattentiveness is endogenized by allowing agents to choose between a costly full-information predictor and a costless sticky-information predictor. This is modeled as a choice between discrete alternatives under rational inattention. Recursive simulation shows that the dynamic equilibrium paths of aggregate variables are highly persistent and match the moments of U.S. data better than a model with fixed sticky information or with sticky prices, especially with regard to higher moments and the degree of persistence. Predictors are chosen in line with the predictions from rational inattention models, as the aggregate degree of attentiveness increases with rising variance of the forecast variable. Moreover, the model can generate hump-shaped impulse responses of inflation to a monetary policy shock if the degree of inattentiveness is sufficiently high.

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Bogomolova, Anna S., et Dmitriy V. Kolyuzhnov. « Economic dynamics under heterogeneous adaptive learning : aggregate economy sufficient conditions for stability ». World of Economics and Management 20, n^o 1 (2020) : 128–53. http://dx.doi.org/10.25205/2542-0429-2020-20-1-128-153.

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We provide sufficient conditions for stability of a linear structurally heterogeneous economy under heterogeneous learning of agents, extending the results of Honkapohja and Mitra (2006), Kolyuzhnov (2011), and Bogomolova and Kolyuzhnov (2019). Sufficient conditions for stability under heterogeneous mixed RLS/SG learning for four classes of models: models without lags and with lags of the endogenous variable and with t or t-1- dating of expectations, are provided for the cases of the diagonal structure of the shock process behaviour or the heterogeneous RLS learning and are presented in terms of structural heterogeneity and are independent of heterogeneity in learning. The results are based on the negative diagonal dominance approach and are provided, first, in terms of the existence of the weights for aggregation of endogenous variables and of expectations across agents, interrelated in a special way, and then in terms of the E-stability of a suitably defined aggregate economy. The fundamental nature of the approach adopted in the paper allows one to apply its results to a vast majority of the existing and prospective linear and linearized economic models (including estimated DSGE models) with adaptive learning of agents.

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14

Giacomini, Raffaella, Vasiliki Skreta et Javier Turen. « Heterogeneity, Inattention, and Bayesian Updates ». American Economic Journal : Macroeconomics 12, n^o 1 (1 janvier 2020) : 282–309. http://dx.doi.org/10.1257/mac.20180235.

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We formulate a theory of expectations updating that fits the dynamics of accuracy and disagreement in a new survey of professional forecasters. We document new stylized facts, including the puzzling persistence of disagreement as uncertainty resolves. Our theory explains these facts by allowing for different channels of heterogeneity. Agents produce an initial forecast based on heterogeneous priors and are heterogeneously “inattentive.” Updaters use Bayes’ rule and interpret public information using possibly heterogeneous models. Structural estimation of our theory supports the conclusion that in normal times heterogeneous priors and inattention are enough to generate persistent disagreement, but not during the crisis. (JEL C53, D81, D83, D84, E31, E37)

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Мутовкина, Н. Ю., N. Yu Mutovkina, Н. А. Семенов, N. A. Semenov, А. Ю. Клюшин et A. Yu Klyushin. « Models of heterogeneous agents’ behavior in a conflict and their implementation algorithms ». Международный журнал "Программные продукты и системы" 29 (1 décembre 2016) : 63–68. http://dx.doi.org/10.15827/0236-235x.116.063-068.

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Acedański, Jan. « Overlapping Generation Models with Heterogeneous Agents and Aggregate Uncertainty in Macroeconomic Modelling ». Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie, n^o 5(941) (2015) : 79–96. http://dx.doi.org/10.15678/znuek.2015.0941.0506.

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17

Boyer, D., O. Miramontes et H. Larralde. « Lévy-like behaviour in deterministic models of intelligent agents exploring heterogeneous environments ». Journal of Physics A : Mathematical and Theoretical 42, n^o 43 (13 octobre 2009) : 434015. http://dx.doi.org/10.1088/1751-8113/42/43/434015.

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Den Haan, Wouter J., Kenneth L. Judd et Michel Juillard. « Computational suite of models with heterogeneous agents : Incomplete markets and aggregate uncertainty ». Journal of Economic Dynamics and Control 34, n^o 1 (janvier 2010) : 1–3. http://dx.doi.org/10.1016/j.jedc.2009.07.001.

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19

Ráfales, Jonatan, et Carlos Vázquez. « Equilibrium models with heterogeneous agents under rational expectations and its numerical solution ». Communications in Nonlinear Science and Numerical Simulation 96 (mai 2021) : 105673. http://dx.doi.org/10.1016/j.cnsns.2020.105673.

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20

Beaumont, Paul M., Yuanying Guan et Alec N. Kercheval. « Complex dynamics in equilibrium asset pricing models with boundedly rational, heterogeneous agents ». Complexity 19, n^o 3 (19 octobre 2013) : 38–55. http://dx.doi.org/10.1002/cplx.21477.

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21

Mann, Richard P. « Evolution of heterogeneous perceptual limits and indifference in competitive foraging ». PLOS Computational Biology 17, n^o 2 (23 février 2021) : e1008734. http://dx.doi.org/10.1371/journal.pcbi.1008734.

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The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.

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22

Lauermann, Stephan, Georg Nöldeke et Thomas Tröger. « The Balance Condition in Search‐and‐Matching Models ». Econometrica 88, n^o 2 (2020) : 595–618. http://dx.doi.org/10.3982/ecta8356.

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Most of the literature that studies frictional search‐and‐matching models with heterogeneous agents and random search investigates steady state equilibria. Steady state equilibrium requires, in particular, that the flows of agents into and out of the population of unmatched agents balance. We investigate the structure of this balance condition, taking agents' matching behavior as given. Building on the “fundamental matching lemma” for quadratic search technologies in Shimer and Smith (2000), we establish existence, uniqueness, and comparative statics properties of the solution to the balance condition for any search technology satisfying minimal regularity conditions. Implications for the existence and structure of steady state equilibria in the Shimer–Smith model and extensions thereof are noted. These reinforce the point that much of the structure of search‐and‐matching models with quadratic search technologies carries over to more general search technologies.

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23

Peralta-Alva, Adrian, et Manuel S. Santos. « PROBLEMS IN THE NUMERICAL SIMULATION OF MODELS WITH HETEROGENEOUS AGENTS AND ECONOMIC DISTORTIONS ». Journal of the European Economic Association 8, n^o 2-3 (5 avril 2010) : 617–25. http://dx.doi.org/10.1111/j.1542-4774.2010.tb00531.x.

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Vilone, Daniele, Timoteo Carletti, Franco Bagnoli et Andrea Guazzini. « The Peace Mediator effect : Heterogeneous agents can foster consensus in continuous opinion models ». Physica A : Statistical Mechanics and its Applications 462 (novembre 2016) : 84–91. http://dx.doi.org/10.1016/j.physa.2016.06.082.

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25

Ure, N. Kemal, Girish Chowdhary, Jonathan P. How et John Vian. « Health Aware Planning Under Uncertainty for Collaborating Heterogeneous Teams of Mobile Agents ». Unmanned Systems 03, n^o 02 (avril 2015) : 89–107. http://dx.doi.org/10.1142/s2301385015500065.

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We consider the problem of solving hybrid discrete-continuous Markov Decision Processes (MDPs) that are often encountered in computing optimal policies for complex multi-agent missions with both continuous vehicle dynamics and discrete mission-state transition models, in the presence of potential health degradations and failures of individual agents. A comprehensive Health Aware Planning (HAP) framework is proposed that establishes a feedback between mission planning and vehicle-level learning-focused adaptive controllers through online learned own models of agent health and capabilities. The HAP framework accounts for predicted likelihood of vehicle health degradations captured through probabilistic state-dependent models that are integrated into the MDP formulation. This proactive ability to anticipate health degradation and plan accordingly enables the HAP approach to consistently outperform planners that change the policies only after failures have occurred (reactive planners). The approach is tested on a large-scale (≈ 1010 state–action pairs) long-duration (persistent) target tracking scenario using a novel on-trajectory planning algorithm, and demonstrated to sustain higher mission performance by reducing the number of failures and re-assessing Unmanned Aerial Vehicle (UAV) capabilities.

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El Abid Amrani, N., O. El Kheir Abra, M. Youssfi et O. Bouattane. « A Novel Deep Learning Approach for Semantic Interoperability Between Heteregeneous Multi-Agent Systems ». Engineering, Technology & ; Applied Science Research 9, n^o 4 (10 août 2019) : 4566–73. http://dx.doi.org/10.48084/etasr.2841.

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This article focuses on the issue of semantic interoperability in heterogeneous distributed multi-agent systems. Existing middleware technologies offer programming models that strongly combine agents’ learning models and communication models, which can lead to performance weaknesses when the number of agents is very important. Moreover, existing methods in the field of semantic interoperability solve the problem of understanding messages exchanged between distributed agents with heterogeneous ontologies, using several techniques to combine these ontologies. The first category of these methods relies on the fusion principle, others use alignment, and finally, there are those founded on Semantic Web technique. All these methods are limited to abstract concepts and do not deal with concrete concepts such as those represented by images. We propose in this paper a new approach that addresses the problem of semantic interoperability between heterogeneous distributed agents based on two principles: At first, the communication aspect of the agent from the learning aspect is separated. Then, we propose extending semantic interoperability to concrete concepts by combining two techniques: Semantic Web technology, which allows terms representing abstract concepts to be interpreted and deep learning technology, which is introduced as a new method to ensure semantic interoperability in the case of concrete concepts such as images. A detailed description of the proposed approach is provided, showing that it is very useful in solving the disadvantages of existing multi-agent platforms.

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GASPAR, JESS, et KENNETH L. JUDD. « SOLVING LARGE-SCALE RATIONAL-EXPECTATIONS MODELS ». Macroeconomic Dynamics 1, n^o 1 (janvier 1997) : 45–75. http://dx.doi.org/10.1017/s1365100597002022.

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We explore alternative approaches to numerical solutions of large rational-expectations models. We discuss and compare several current alternatives, focusing on the trade-offs in accuracy, space, and speed. The models range from representative-agent models with many goods and capital stocks, to models of heterogeneous agents with complete or incomplete asset markets. The methods include perturbation and projection methods. We show that these methods are capable of analyzing moderately large models even when we use only elementary, general-purpose numerical methods.

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Bogomolova, A. S., et D. V. Kolyuzhnov. « Economic Dynamics under Heterogeneous Adaptive Learning : General Criteria and Sufficient Conditions for Stability ». World of Economics and Management 19, n^o 4 (2019) : 87–103. http://dx.doi.org/10.25205/2542-0429-2019-19-4-87-103.

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The article extends the results of Honkapohja and Mitra (2006) and Kolyuzhnov (2011) and provides criteria and sufficient conditions for stability in a structurally heterogeneous economy under heterogeneous adaptive learning of agents. The criteria for stability under heterogeneous mixed RLS/SG learning for four classes of models – without lags and with lags of the endogenous variable and with t or t – 1 – dating of expectations – and sufficient conditions for stability for the cases of the diagonal structure of the shock process behavior or the heterogeneous RLS learning are presented in terms of the corresponding Jacobian matrices. In addition, the study presents a very useful criterion for the stability for all types of models under mixed RLS/SG learning with equal degrees of inertia for each type of learning algorithm in terms of stability of a suitably defined average economy with two agents. The derived criteria and sufficient conditions for stability are based on the results of the theory of stochastic approximation and are presented in terms of mixture of structural and learning heterogeneity, which are essential to get sufficient and necessary conditions for stability irrespective of heterogeneity in learning presented in terms of E-stability of suitably defined aggregate economies, the “same sign” conditions and the E-stability of a suitably defined average economy and its subeconomies. The fundamental nature of the approach adopted in the paper makes it possible to apply the results to a vast majority of the existing and prospective linear and linearized economic models (including estimated DSGE models) with adaptive learning of agents.

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Harré, Michael S., Aleksey Eremenko, Kirill Glavatskiy, Michael Hopmere, Leonardo Pinheiro, Simon Watson et Lynn Crawford. « Complexity Economics in a Time of Crisis : Heterogeneous Agents, Interconnections, and Contagion ». Systems 9, n^o 4 (15 octobre 2021) : 73. http://dx.doi.org/10.3390/systems9040073.

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In this article, we consider a variety of different mechanisms through which crises such as COVID-19 can propagate from the micro-economic behaviour of individual agents through to an economy’s aggregate dynamics and subsequently spill over into the global economy. Our central theme is one of changes in the behaviour of heterogeneous agents, agents who differ in terms of some measure of size, wealth, connectivity, or behaviour, in different parts of an economy. These are illustrated through a variety of case studies, from individuals and households with budgetary constraints, to financial markets, to companies composed of thousands of small projects, to companies that implement single multi-billion dollar projects. In each case, we emphasise the role of data or theoretical models and place them in the context of measuring their inter-connectivity and emergent dynamics. Some of these are simple models that need to be ‘dressed’ in socio-economic data to be used for policy-making, and we give an example of how to do this with housing markets, while others are more similar to archaeological evidence; they provide hints about the bigger picture but have yet to be unified with other results. The result is only an outline of what is possible but it shows that we are drawing closer to an integrated set of concepts, principles, and models. In the final section, we emphasise the potential as well as the limitations and what the future of these methods hold for economics.

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BEZEMER, DIRK J. « THE ECONOMY AS A COMPLEX SYSTEM : THE BALANCE SHEET DIMENSION ». Advances in Complex Systems 15, supp02 (septembre 2012) : 1250047. http://dx.doi.org/10.1142/s0219525912500476.

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Given the economy's complex behavior and sudden transitions as evidenced in the 2007–2008 crisis, agent-based models are widely considered a promising alternative to current macroeconomic research dominated by DSGE models. Their failure is commonly interpreted as a failure to incorporate heterogeneous interacting agents. This paper explains that complex behavior and sudden transitions also arise from the economy's financial structure as reflected in its balance sheets, not just from heterogeneous interacting agents. It introduces "flow-of-funds" or "accounting" models, which were pre eminent in successful anticipations of the recent crisis. In illustration, a simple balance sheet model of the economy is developed to demonstrate that non-linear behavior and sudden transition may arise from the economy's balance sheet structure, even without any micro-foundations. The paper concludes by discussing one recent example of combining flow-of-funds and agent-based models. This appears a promising avenue for future research.

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Hayward, Serge. « The Role of Heterogeneous Agents’ Past and Forward Time Horizons in Formulating Computational Models ». Computational Economics 25, n^o 1-2 (février 2005) : 25–40. http://dx.doi.org/10.1007/s10614-005-6246-0.

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Badshah, Muffasir, Paul Beaumont et Anuj Srivastava. « Computing Equilibrium Wealth Distributions in Models with Heterogeneous-Agents, Incomplete Markets and Idiosyncratic Risk ». Computational Economics 41, n^o 2 (6 janvier 2012) : 171–93. http://dx.doi.org/10.1007/s10614-011-9313-8.

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Den Haan, Wouter J. « Assessing the accuracy of the aggregate law of motion in models with heterogeneous agents ». Journal of Economic Dynamics and Control 34, n^o 1 (janvier 2010) : 79–99. http://dx.doi.org/10.1016/j.jedc.2008.12.009.

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Battu, Balaraju, et Narayanan Srinivasan. « Evolution of conditional cooperation in public good games ». Royal Society Open Science 7, n^o 5 (mai 2020) : 191567. http://dx.doi.org/10.1098/rsos.191567.

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Cooperation declines in repeated public good games because individuals behave as conditional cooperators. This is because individuals imitate the social behaviour of successful individuals when their payoff information is available. However, in human societies, individuals cooperate in many situations involving social dilemmas. We hypothesize that humans are sensitive to both success (payoffs) and how that success was obtained, by cheating (not socially sanctioned) or good behaviour (socially sanctioned and adds to prestige or reputation), when information is available about payoffs and prestige. We propose and model a repeated public good game with heterogeneous conditional cooperators where an agent's donation in a public goods game depends on comparing the number of donations in the population in the previous round and with the agent's arbitrary chosen conditional cooperative criterion. Such individuals imitate the social behaviour of role models based on their payoffs and prestige. The dependence is modelled by two population-level parameters: affinity towards payoff and affinity towards prestige . These affinities influence the degree to which agents value the payoff and prestige of role models. Agents update their conditional strategies by considering both parameters. The simulations in this study show that high levels of cooperation are established in a population consisting of heterogeneous conditional cooperators for a certain range of affinity parameters in repeated public good games. The results show that social value (prestige) is important in establishing cooperation.

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Li, Ying, Hongduo Cao et Genfeng Wen. « Simulation study on opinion formation models of heterogeneous agents based on game theory and complex networks ». SIMULATION 93, n^o 11 (25 mai 2017) : 899–919. http://dx.doi.org/10.1177/0037549717709349.

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This study investigates a new opinion formation model of heterogeneous agents, a network stubborn individuals and orators (NSO) model based on game theory and complex social networks. Game theory solves economists’ rational choice-making problems, and complex social networks reflect the social impact on opinion evolution. The NSO model involves both social and individual heterogeneous characteristics. In a society, the more unequal the members, and the closer the social distances, the faster opinions spread. In the real world, the power-law degree distribution and the short paths in social networks can generate the rapid spread of an opinion. This study also investigates opinion control under the NSO model. The results show that opinion guidance is most likely to separate the public into different groups rather than converge to the guide’s opinion.

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Lopez-Jimenez, Jorge, Nicanor Quijano et Alain Vande Wouwer. « An Agent-Based Crop Model Framework for Heterogeneous Soils ». Agronomy 11, n^o 1 (4 janvier 2021) : 85. http://dx.doi.org/10.3390/agronomy11010085.

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Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

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Kirman, Alan P. « Whom or What Does the Representative Individual Represent ? » Journal of Economic Perspectives 6, n^o 2 (1 mai 1992) : 117–36. http://dx.doi.org/10.1257/jep.6.2.117.

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Macroeconomic models often assume that the choices of all the diverse agents in one sector— consumers for example—can be considered as the choices of one “representative” standard utility maximizing individual whose choices coincide with the aggregate choices of the heterogeneous individuals. My basic point is that the reduction of the behavior of a group of heterogeneous agents even if they are all themselves utility maximizers, is not simply an analytical convenience as often explained, but is both unjustified and leads to conclusions which are usually misleading and often wrong. First, such models are particularly ill-suited to studying macroeconomic problems like unemployment, which should be viewed as coordination failures. Furthermore these models, instead of being a hive of activity and exchange, are frequently, ones in which no trade at all takes place. And this is just the beginning of a list of problems with this approach. Finally I will consider more positive alternatives to the representative individual approach—approaches that focus on heterogeneity of agents may and interaction between individuals. It is clear that the “representative” agent deserves a decent burial, as an approach to economic analysis that is not only primitive, but fundamentally erroneous.

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LEDZEWICZ, URSZULA, et HEINZ SCHÄTTLER. « ON OPTIMAL CHEMOTHERAPY FOR HETEROGENEOUS TUMORS ». Journal of Biological Systems 22, n^o 02 (juin 2014) : 177–97. http://dx.doi.org/10.1142/s0218339014400014.

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A mathematical model for cancer chemotherapy of heterogeneous tumor populations is considered as an optimal control problem with the objective to minimize the tumor burden over a prescribed therapy horizon. While an upfront maximum tolerated dose (MTD) regimen with rest-period has been confirmed as mathematically optimal for models when the tumor population is homogeneous, in the presence of partially sensitive or even resistant cells, protocols that administer the therapeutic agents at lower dose rates described by so-called singular controls become a viable alternative. In this paper, the structure of protocols that follow an initial upfront maximum dose treatment with reduced dose rate singular controls is investigated. Such protocols reflect structures which in the medical literature sometimes are called chemo-switch protocols.

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Becker, Robert A., et Tapan Mitra. « EFFICIENT RAMSEY EQUILIBRIA ». Macroeconomic Dynamics 16, S1 (9 novembre 2011) : 18–32. http://dx.doi.org/10.1017/s1365100511000538.

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Ramsey equilibrium models with heterogeneous agents and borrowing constraints are shown to yield efficient equilibrium sequences of aggregate capital and consumption. The proof of this result is based on verifying that equilibrium sequences of prices satisfy the Malinvaud criterion for efficiency.

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Isaza, Gustavo, Maria H. Mejía, Luis Fernando Castillo, Adriana Morales et Nestor Duque. « Network Management using Multi-Agents System ». ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal 1, n^o 3 (1 juillet 2013) : 49–54. http://dx.doi.org/10.14201/adcaij20121314954.

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This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision.

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Yang, Hongyong, Fujun Han, Mei Zhao, Shuning Zhang et Jun Yue. « Distributed containment control of heterogeneous fractional-order multi-agent systems with communication delays ». Open Physics 15, n^o 1 (3 août 2017) : 509–16. http://dx.doi.org/10.1515/phys-2017-0058.

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AbstractBecause many networked systems can only be characterized with fractional-order dynamics in complex environments, fractional-order calculus has been studied deeply recently. When diverse individual features are shown in different agents of networked systems, heterogeneous fractional-order dynamics will be used to describe the complex systems. Based on the distinguishing properties of agents, heterogeneous fractional-order multi-agent systems (FOMAS) are presented. With the supposition of multiple leader agents in FOMAS, distributed containment control of FOMAS is studied in directed weighted topologies. By applying Laplace transformation and frequency domain theory of the fractional-order operator, an upper bound of delays is obtained to ensure containment consensus of delayed heterogenous FOMAS. Consensus results of delayed FOMAS in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.

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Boyd, Jennifer, Rebekah Wilson, Corinna Elsenbroich, Alison Heppenstall et Petra Meier. « Agent-Based Modelling of Health Inequalities following the Complexity Turn in Public Health : A Systematic Review ». International Journal of Environmental Research and Public Health 19, n^o 24 (14 décembre 2022) : 16807. http://dx.doi.org/10.3390/ijerph192416807.

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There is an increasing focus on the role of complexity in public health and public policy fields which has brought about a methodological shift towards computational approaches. This includes agent-based modelling (ABM), a method used to simulate individuals, their behaviour and interactions with each other, and their social and physical environment. This paper aims to systematically review the use of ABM to simulate the generation or persistence of health inequalities. PubMed, Scopus, and Web of Science (1 January 2013–15 November 2022) were searched, supplemented with manual reference list searching. Twenty studies were included; fourteen of them described models of health behaviours, most commonly relating to diet (n = 7). Six models explored health outcomes, e.g., morbidity, mortality, and depression. All of the included models involved heterogeneous agents and were dynamic, with agents making decisions, growing older, and/or becoming exposed to different health risks. Eighteen models represented physical space and in eleven models, agents interacted with other agents through social networks. ABM is increasingly contributing to our understanding of the socioeconomic inequalities in health. However, to date, the majority of these models focus on the differences in health behaviours. Future research should attempt to investigate the social and economic drivers of health inequalities using ABM.

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IRLE, ALBRECHT, JONAS KAUSCHKE, THOMAS LUX et MISHAEL MILAKOVIĆ. « SWITCHING RATES AND THE ASYMPTOTIC BEHAVIOR OF HERDING MODELS ». Advances in Complex Systems 14, n^o 03 (juin 2011) : 359–76. http://dx.doi.org/10.1142/s0219525911002949.

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Markov chains have experienced a surge of economic interest in the form of behavioral agent-based models that aim at explaining the statistical regularities of financial returns. We review some of the relevant mathematical facts and show how they apply to agent-based herding models, with the particular goal of establishing their asymptotic behavior since several studies have pointed out that the ability of such models to reproduce the stylized facts hinges crucially on the size of the agent population (typically denoted by N), a phenomenon that is also known as N-dependence. Our main finding is that N-(in)dependence traces back to both the topology and the velocity of information transmission among heterogeneous financial agents.

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de Carvalho Bertoli, Gustavo, Lourenço Alves Pereira Júnior et Osamu Saotome. « Improving detection of scanning attacks on heterogeneous networks with Federated Learning ». ACM SIGMETRICS Performance Evaluation Review 49, n^o 4 (2 juin 2022) : 118–23. http://dx.doi.org/10.1145/3543146.3543172.

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Scanning attacks are the first step in the attempt to compromise the security of systems. Machine learning (ML) has been used for network intrusion detection systems (NIDS) to protect systems by learning misbehavior based on network traffic. This paper demonstrates that Federated Learning (FL) is a promising approach to achieve better detection performance than traditional local training and inference on distributed agents. Also, this FL approach brings privacy, efficiency, and it is suitable for distributed ML-based NIDS solutions. We present a horizontal FL setup using Logistic Regression with FedAvg strategy applied to 13 agents (data silos) capable of providing an iterative process of constant learning improvement. Our results indicate a more stable learning process when observed the F1-score average, whereas the traditional NIDS approach (local trained models) present lesser performance and bigger variability to classify scanning and benign traffic. We tested our model performance on the TON_IoT dataset containing network traffic from a virtualized heterogeneous network composed of cloud, fog, and edge layers.

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de Carvalho Bertoli, Gustavo, Lourenço Alves Pereira Júnior et Osamu Saotome. « Improving detection of scanning attacks on heterogeneous networks with Federated Learning ». ACM SIGMETRICS Performance Evaluation Review 49, n^o 4 (2 juin 2022) : 118–23. http://dx.doi.org/10.1145/3543146.3543172.

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Scanning attacks are the first step in the attempt to compromise the security of systems. Machine learning (ML) has been used for network intrusion detection systems (NIDS) to protect systems by learning misbehavior based on network traffic. This paper demonstrates that Federated Learning (FL) is a promising approach to achieve better detection performance than traditional local training and inference on distributed agents. Also, this FL approach brings privacy, efficiency, and it is suitable for distributed ML-based NIDS solutions. We present a horizontal FL setup using Logistic Regression with FedAvg strategy applied to 13 agents (data silos) capable of providing an iterative process of constant learning improvement. Our results indicate a more stable learning process when observed the F1-score average, whereas the traditional NIDS approach (local trained models) present lesser performance and bigger variability to classify scanning and benign traffic. We tested our model performance on the TON_IoT dataset containing network traffic from a virtualized heterogeneous network composed of cloud, fog, and edge layers.

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Coutinho, Luciano R., Anarosa A. F. Brandão, Olivier Boissier et Jaime S. Sichman. « Towards Agent Organizations Interoperability : A Model Driven Engineering Approach ». Applied Sciences 9, n^o 12 (13 juin 2019) : 2420. http://dx.doi.org/10.3390/app9122420.

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In the research and development of multiagent systems (MAS), one of the central issues is how to conciliate the autonomy of the agents with a desirable and stable behavior of the MAS as a whole. Agent organizations have been proposed as a suitable metaphor for engineering social order in MAS. However, this emphasis has led to several proposals of organizational models for MAS design, thus creating an organizational interoperability problem: How to ensure that agents, possibly designed to work with different organizational models, could interact and collectively solve problems? In this paper, we have adopted techniques from Model Driven Engineering to handle this problem. In particular, we propose an abstract and integrated view of the main concepts that have been used to specify agent organizations, based on several organizational models present in the literature. We apply this integrated view to design MAORI, a model-based architecture for organizational interoperability. We present a MAORI application example that has shown that our approach is computationally feasible, enabling agents endowed with heterogeneous organizational models to cooperatively solve a problem.

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Magnani, Riccardo, et Jean Mercenier. « On linking microsimulation and computable general equilibrium models using exact aggregation of heterogeneous discrete-choice making agents ». Economic Modelling 26, n^o 3 (mai 2009) : 560–70. http://dx.doi.org/10.1016/j.econmod.2008.12.002.

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Taberna, Alessandro, Tatiana Filatova, Debraj Roy et Brayton Noll. « Tracing resilience, social dynamics and behavioral change : a review of agent-based flood risk models ». Socio-Environmental Systems Modelling 2 (8 décembre 2020) : 17938. http://dx.doi.org/10.18174/sesmo.2020a17938.

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Climate change and rapid urbanization exacerbate flood risks worldwide. The recognition of the crucial role that human actors play in altering risks and resilience of flood-prone cities triggers a paradigm shift in climate risks assessments and drives the proliferation of computational models that include societal dynamics. Yet, replacing a representative rational actor dominant in climate policy models with a variety of behaviorally-rich agents that interact, learn, and adapt is not straightforward. Focusing on the costliest climate-exacerbated hazard, flooding, we review computational agent-based models that include behavioral change and societal dynamics. We distinguish between two streams of literature: one stemming from economics & behavioral sciences and another from hydrology. Our findings show that most studies focus on households while representing decisions of other agents (government, insurance, urban developers) simplistically and entirely overlooking firms' choices in the face of risks. The two communities vary in the extent they ground agents' rules in social theories and behavioral data when modeling boundedly-rational decisions. While both aspire to trace feedbacks that agents collectively instigate, they employ different learning and interactions when computing societal dynamics in the face of climate risks. Dynamics of hazard, exposure, and vulnerability components of flood risks driven by incremental adaptation of agents are well represented. We highlight that applying a complex adaptive system perspective to trace the evolution of resilience can lead to a better understanding of transformational adaptation. The methodological advances in computational models with heterogeneous behaviorally-rich adaptive agents are relevant for adaptation to different climate-driven hazards beyond flooding.

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LORENZ, JAN. « CONTINUOUS OPINION DYNAMICS UNDER BOUNDED CONFIDENCE : A SURVEY ». International Journal of Modern Physics C 18, n^o 12 (décembre 2007) : 1819–38. http://dx.doi.org/10.1142/s0129183107011789.

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Models of continuous opinion dynamics under bounded confidence have been presented independently by Krause and Hegselmann and by Deffuant et al. in 2000. They have raised a fair amount of attention in the communities of social simulation, sociophysics and complexity science. The researchers working on it come from disciplines such as physics, mathematics, computer science, social psychology and philosophy. In these models agents hold continuous opinions which they can gradually adjust if they hear the opinions of others. The idea of bounded confidence is that agents only interact if they are close in opinion to each other. Usually, the models are analyzed with agent-based simulations in a Monte Carlo style, but they can also be reformulated on the agent's density in the opinion space in a master equation style. The contribution of this survey is fourfold. First, it will present the agent-based and density-based modeling frameworks including the cases of multidimensional opinions and heterogeneous bounds of confidence. Second, it will give the bifurcation diagrams of cluster configuration in the homogeneous model with uniformly distributed initial opinions. Third, it will review the several extensions and the evolving phenomena which have been studied so far, and fourth it will state some open questions.

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Hommes, Cars, et Thomas Lux. « INDIVIDUAL EXPECTATIONS AND AGGREGATE BEHAVIOR IN LEARNING-TO-FORECAST EXPERIMENTS ». Macroeconomic Dynamics 17, n^o 2 (9 décembre 2011) : 373–401. http://dx.doi.org/10.1017/s1365100511000162.

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Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations and individual forecasting behaviour in recent learning-to-forecast laboratory experiments with human subjects (Hommes et al. 2007), simultaneously and across different treatments.

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