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2004, Lilia Rejeb,
Using adaptive multi-agent systems to simulate economic models
Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004., New York, NY, USA, 2004, pp. 68-75., 2004
Abstract
Economic markets are complex systems. They are characterized by a large and dynamic population of firms. To deal with this complexity, we propose an adaptive multiagent system which models a set of firms in competition with each other within a shared market. The firms are represented by agents; each firm is represented by an adaptive agent. We show the advantages of adaptive agents to represent firms. Moreover, we underline the limits of the economic models which account for the firms only and ignore the organizational forms. We propose a new adaptive multiagent model that includes the organizational forms into the economic models. We simulate this model and discuss its advantages.
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2003Nadia Ben Azzouna,
Analysis of ADSL traffic on an IP backbone link
GLOBECOM'03. IEEE Global Telecommunications Conference (IEEE Cat. No. 03CH37489), 2003
Abstract
Measurements from an Internet backbone link carrying TCP traffic towards different ADSL areas are analyzed. For traffic analysis, we adopt a flow based approach and the popular mice/elephants dichotomy, where mice refer to short traffic transfers and elephants to long transfers. The originality of the reported experimental data, when compared with previous measurements from very high speed backbone links, is that the commercial traffic includes a significant part generated by peer-to-peer applications. This kind of traffic exhibits some remarkable properties in terms of mice and elephants, as we describe. It turns out that by adopting a suitable level of aggregation, the bit rate of mice can be described by means of a Gaussian process. The bit rate of elephants is smoother than that of mice and can also be well approximated by a Gaussian process.
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2002Lamjed Ben Said, ,
Agent-based interaction analysis of consumer behavior
AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1 Pages 184 - 190, 2002
Abstract
Our goal is to create a virtual consumer population that can be used for simulating the effects of marketing strategies in a competing market context. That requires having a consumers’ behavioral model allowing the representation of observed individual behaviors and the simulation of a large population of consumers. That also requires finding the parameters’ values characterizing the virtual population that reproduces real market evolutions. This paper proposes a consumer behavioral model based on a set of behavioral primitives such as imitation, conditioning and innovativeness, which are founded on the new concept of behavioral attitude. It shows that this model provides an interpretation of the main concepts and cognitive features, issued from marketing research and psycho-sociology works on consumption. The paper presents also the CUstomer BEhavior Simulator (CUBES), which has been realized for implementing the customer model and leading multi-agents simulations. It shows how genetic algorithms (GA), in addition to multi-agent systems, are used to fit the characteristics of the virtual consumers’ population into a global realistic market behavior.
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2001Lamjed Ben Said,
Multi-Agent Simulation of Virtual Consumer Populations in a Competitive Market
In Proceedings of the 10th European Workshop on Multi-Agent Systems, Modelling Autonomous Agents in A Multi-Agent Word. Annecy, France, May (Vol. 2, No. 4, pp. 31-43)., 2001
Abstract
No abstract available.
Lamjed Ben Said, ,Multi-agent based simulation of consumer behaviour: Towards a new marketing approach
In International Congress on Modelling and Simulation Proceedings., 2001
Abstract
Theoretical concepts dealing with consumer behaviour issues from studies led in various research areas: marketing, psychology, sociology and economics. This paper presents a multi-agent simulation of consumer behaviour based on an integrating approach. Our goal is to create virtual populations including several thousands of artificial consumers that exhibit realistic behaviours in the context of a competing market. These populations are used to test the effects of marketing strategies. Existing consumer behavioural models are not well suited for the realization of such market simulations including a large number of artificial consumers. In this work a consumer behavioural model based on the concept of behavioural attitude is introduced to solve this problem. It proposes to integrate and organize most of the fundamental notions elaborated within the aforementioned research areas.
