Modelling a Centralized Academic Labour Market: Efficiency and Fairness

International audienceA formalization of the centralized French Academic Labour Market in terms of Multi-Agent System is presented. Extensive simulations are used to investigate typical and possible regimes of the system, supporting a sensitivity analysis of the main parameters of the model, such as the applicative pressure and the preference bias towards local candidates. Based on the calibration of the parameters of the abstract model after the information disclosed from o±cial sources, some positive and normative results are presented. Three prototypical settings are distinguished: the equilibrium setting corresponds to the perfect market case, where each candidate interacts with each University; the Humanities and Sciences setting; and the Law and Management setting. The differences between the last two settings concern both the applicative pressure (number of candidate per academic position) and the scope of each candidate (interacting with few or many Universities). Counter-intuitive findings, related in particular to the role of the preference biases, are presented and discussed

Description automatique de dynamiques de groupes dans des simulations à base d'agents

ISBN 978-2-36493-037-7National audienceMulti agent based simulations (MABS) have been successfully exploited to model complex systems in different areas. Nevertheless a pitfall of MABS is that their complexity increases with the number of agents and the number of different types of behaviours considered in the model. For average and large systems it is impossible to validate the trajectories of single agents in a simulation. The classical validation approaches, where only global indicators are evaluated, are too simplistic to give enough confidence on the simulation's model. It is then necessary to introduce intermediate levels of validation. In this paper we propose the use of data clustering and automated characterization of clusters in order to build, describe and follow the evolution of groups of agents in simulations. The description of clusters is used to generate profiles of agents that are reintroduced in simulations in order to study the stability of the descriptions and structures of clusters over several simulations and decide their capability to describe the modelled phenomena. These tools provides the modeller with an intermediate point of view on the evolution of the model. They are flexible enough to be applied both offline and online, and we illustrate it with both a NetLogo and a CSV-simulation log example

SimAnalyzer: automated description of groups dynamics in agent-based simulations

International audienceMulti agent based simulations (MABS) have been successfully exploited to model complex systems in different areas. Nevertheless a pitfall of MABS is that their complexity increases with the number of agents and the number of different types of behaviours considered in the model. For average and large systems it is impossible to validate the trajectories of single agents in a simulation. The classical validation approaches, where only global indicators are evaluated, are too simplistic to give enough confidence on the simulation's model. It is then necessary to introduce intermediate levels of validation. In this paper we propose the use of data clustering and automated characterization of clusters in order to build, describe and follow the evolution of groups of agents in simulations. The description of clusters is used to generate profiles of agents that are reintroduced in simulations in order to study the stability of the descriptions and structures of clusters over several simulations and decide their capability to describe the modelled phenomena. These tools provides the modeller with an intermediate point of view on the evolution of the model. They are flexible enough to be applied both offline and online, and we illustrate it with both a NetLogo and a CSV-simulation log example

Automated observation of multi-agent based simulations: a statistical analysis approach

International audienceMulti-agent based simulations (MABS) have been successfully used to model complex systems in different areas. Nevertheless a pitfall of MABS is that their complexity increases with the number of agents and the number of different types of behavior considered in the model. For average and large systems, it is impossible to validate the trajectories of single agents in a simulation. The classical validation approaches, where only global indicators are evaluated, are too simplistic to give enough confidence in the simulation. It is then necessary to introduce intermediate levels of validation. In this paper we propose the use of data clustering and automated characterization of clusters in order to build, describe and follow the evolution of groups of agents in simulations. These tools provides the modeler with an intermediate point of view on the evolution of the model. Those tools are flexible enough to allow the modeler to define the groups level of abstraction (i.e. the distance between the groups level and the agents level) and the underlying hypotheses of groups formation. We give an online application on a simple NetLogo library model (Bank Reserves) and an offline log application on a more complex Economic Market Simulation

Which Buyer-Supplier Strategies on Uncertain Markets? A Multi-Agents Simulation

International audienceThe relationship the firm has with its clients and suppliers largely determines the amount of value it is able to capture in the chain. Yet little is known about the impact of market uncertainty on the choice of the best buyer-supplier strategy in terms of value appropriation. The paper proposes to investigate which among different types of strategies bring more value to the buyer when market uncertainty increases. It relies on a very innovative method of multi-agents simulation based on an in-depth ethnographic observation phase of a real market in France. It shows that pure loyalty is not necessarily the best strategy when market uncertainty increases and that the buyer may face a dilemma between maximizing the margin rate and ensuring regularity of supply

Negotiation protocols and dynamic social networks

International audienceMulti-agent system make it possible to investigate systems with complex interaction protocols and limited information sharing. Our objective in this paper is to emphasize the impact of exchange protocols in social networks. The presented MAS considers a loan-granting scenario where each agent can borrow/lend money to its neighbors and/or consume it. We define six interaction protocols, ranging from fixed equilibrium rate loans to double-free auctions, and we study their impact on the network structure and the global welfare of the economy. Further, the agent fitness is investigated in relation with its connectivity (number of neighbors) and eccentricity (longest path to the other agents)

Multi-agent Based simulation for Decision-Making: an application to Rungis food market

International audienceIn this paper, we present our first results obtained with a multi-agent based simulation of the fruit and vegetable Rungis market. Our goal is to simulate negotiation and price formation based on observed strategies on the real market. We aim to understand negotiation and price formation mechanisms, and explain their impact on macro variables (like the difference between the official price and the average price used on the market)

Economy-driven Shaping of Social Networks and Emerging Class Behaviors

International audienceIn this paper, we propose an agent-based analysis of a cumulative social-network game. Agents grant loans to their neighbours to maximize their intertemporal utility function. With a complete graph, we show that interest rates converge toward the theoretical equilibrium, even if ther is no centralized walrasian auctioneer and no preference transmition between agents. With a dynamic network, we explain why the network can't stabilize with a rational strategy. We introduce death and show that, even if the rational strategy is individually the best, the situation where three different strategies coexist is better for the global welfare

Prêts bilatéraux et réseaux sociaux

International audienceIn this paper, our goal is to use Agent-Based Computational Economics and traditional economic methodology to study a path-dependent context: loan granting in a dynamicsocial network with intertemporal utility functions. We study the evolution of the graph andmacro variables, and show that interest rate converge even if the network is locally unstable.We also study the impact of agent strategies on global welfare of the economy, and concludethat a diversity of strategies increases global welfare.Dans cet article, nous étudions l'évolution d'un réseau social dans lequel des agents réalisent des prêts bilatéraux guidés par leurs préférences intertemporelles. Nous étudions l'évolution du graphe et de variables macroéconomiques et montrons notamment que le taux d'intérêt converge malgré une instabilité locale du graphe. Puis nous nous intéressons au bien être global de l'économie dans le cas où les agents disposent d'une stratégie pour déterminer leurs liens sociaux et montrons en particulier, dans le cas ou les agents sont mortels, que la diversité des stratégies conduit à un accroissement du bien être collectif