Jean-Daniel Kant

Modeling one human decision maker with a multi-agent system: the CODAGE approach

In this paper, we propose an agent-based model of human decision making: CODAGE (Cognitive Decision AGEnt). Classical Decision Theories have been widely used in multi-agent systems, but imply a too rational behavior when faced with real-world human data. Moreover, classical model usually exceeds human capabilities. Therefore, we derived our decision model from several cognitive psychological theories (e.g. Simons decision theory, Montgomerys search of dominance structure, etc.) to take human bounded rationality into account. While most of existing cognitive agents use the BDI framework, we propose a new kind of architecture. In the CODAGE model, the decision maker is modeled by an entire multi-agent system, where each agent is in charge a particular sub-process of the whole decision. The architecture is intended to be as generic as possible. It could be viewed as an agent-based decision framework, in which different decision heuristics and biases could be implemented. We illustrate this approach with a simulation of a small experimental financial market, for which our model was able to replicate some human decision behaviors.

Using Associative Networks To Represent Adopters' Beliefs In A Multiagent Model Of Innovation Diffusion

A lot of agent-based models were built to study diffusion of innovations. In most of these models, beliefs of individuals about the innovation were not represented at all, or in a highly simplified way. In this paper, we argue that representing beliefs could help to tackle problematics identified for diffusion of innovations, like misunderstanding of information, which can lead to diffusion failure, or diffusion of linked inventions. We propose a formalization of beliefs and messages as associative networks. This representation allows one to study the social representations of innovations and to validate diffusion models against real data. It could also make models usable to analyze diffusion prior to the product launch. Our approach is illustrated by a simulation of iPod™ diffusion.

Forbidding Fixed Duration Contracts: Unfolding the Opposing Consequences with a Multi-Agent Model of the French Labor Market

The model WorkSim is a new tool of analysis for the French labor market. The two main novelties of the model are that it simulates the gross flows of workers between different states (unemployment, employment, inactivity) on the basis of the rational decisions of individual heterogeneous agents, and that both firms and individuals are represented. The model is calibrated by an optimization algorithm, in order to reproduce the situation of the French labor market in 2011. In the present paper, we focus on experiments dealing with the suppression of the fixed duration contracts (FDC) and we unfold the opposing consequences of FDC on unemployment.

From Beliefs to Attitudes: Polias, a Model of Attitude Dynamics Based on Cognitive Modeling and Field Data

Attitude is a key concept in social psychology. The paper presents a novel agent-based model to simulate attitude formation by combining a rational and an emotional components based on cognitive, psychological and social theories. Individuals of the artificial population perceive actions taken by actors such as government or brands, they form an attitude toward them and also communicate the events through a social network. The model outputs are first studied through a functional analysis in which some unique macroscopic behaviors have emerged such as the impact of social groups, the resistance of the population toward disinformation campaigns or the social pressure. We then applied our model on a real world scenario depicting the effort of French Forces in their stabilization operations in Kapisa (Afghanistan) between 2010 and 2012. We calibrated the model parameters based on this scenario and the results of opinion polls that were conducted in the area during the same period about the sentiment of the population toward the Forces. Our model was able to reproduce polls results with a global error under 3%. Based on these results, we show the different dynamics tendencies that emerged among the population by applying a non-supervised classification algorithm.

Modélisation de l'impact des croyances et de la communication sur la formation et la dynamique des attitudes : une approche multi-agent.

Cet article presente un modele de simulation multi-agent permettant d’etudier la formation et la dynamique des attitudes basees sur la perception des individus ainsi que sur la diffusion de l’information par le biais de la communication. Nous presentons l’attitude comme etant un ensemble d’associations entre l’objet social et ses evaluations d’intensite variable, comme le propose Fazio [11]. Nous illustrons le role de la communication sur la dynamique des attitudes au travers de plusieurs experimentations.