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2010Saoussen Bel Haj Kacem, ,
Approximate Reasoning based on Linguistic Modifiers in a Learning System
ICSOFT (2). 2010., 2010
Abstract
Approximate reasoning, initially introduced in fuzzy logic context, allows reasoning with imperfect knowledge. We have proposed in a previous work an approximate reasoning based on linguistic modifiers in a symbolic context. To apply such reasoning, a base of rules is needed. We propose in this paper to use a supervised learning system named SUCRAGE, that automatically generates multi-valued classification rules. Our reasoning is used with this rule base to classify new objects. Experimental tests and comparative study with two initial reasoning modes of SUCRAGE are presented. This application of approximate reasoning based on linguistic modifiers gives satisfactory results. Besides, it provides a comfortable linguistic interpretation to the human mind thanks to the use of linguistic modifiers.
Islem Henane, Lamjed Ben Said, ,Multi-agent Based Simulation of Animal Food Selective Behavior in a Pastoral System
In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2010. Lecture Notes in Computer Science(), vol 6070. Springer, Berlin, Heidelberg., 2010
Abstract
Pastoral systems are considered as complex systems, given the number of entities and the multitude of interactions and levels of granularity. To conduct a study of such system taking into account the interactions and their results, analytical approaches are not adequate. In this paper, we present an agent-based model of the animal behavior in the pastoral system taking into account the selective food aspect. This model has been validated using a multi-agent based simulation implemented on the simulation platform Cormas. The obtained results reflect the importance of this aspect in the animal behavior and its effects on vegetation cover.
Zahra Kodia, Lamjed Ben Said,Towards a new cognitive modeling approach for multi-agent based simulation of stock market dynamics, (short paper)
Proc. of 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010. pp. 1565-1566, Toronto Canada., 2010
Abstract
This paper introduces a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Interactions between investors and information exchange during a transaction reproduce the market dynamics and organize the multi-agent based pricing.
Zahra Kodia, Lamjed Ben Said,A multi-agent based pricing: a virtual stock market simulation
8ème ENIM IFAC Conférence Internationale de Modélisation et Simulation (MOSIM’2010), Mai 2010. Hammamet, Tunisia, 2010
Abstract
We introduce in this paper a new conceptual model representing the stock market dynamics.
This model is essentially based on cognitive behavior of the investors. In order to validate our model, we
build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator
is composed of market supervisor agent essentially responsible for executing transactions via an order
book and various kinds of investor agents depending to their profile. The purpose of this simulation is to
understand the influence of psychological character of an investor and its neighborhood on its decision-making
and their impact on the market in terms of price fluctuations. Interactions between investors and information
exchange during a transaction reproduce the market dynamics and organize the multi-agent based pricing.Zahra Kodia, Lamjed Ben Said,A Study of Stock Market Trading Behavior and Social Interactions through a Multi Agent Based Simulation
Agent and Multi-Agent Systems: Technologies and Applications, 4th KES International Symposium, KES-AMSTA 2010, June 23-25, 2010, Proceedings. Part II pp. 302-311, Gdynia, Poland., 2010
Abstract
In this paper, we study the stock market trading behavior and the interactions between traders. We propose a novel model which includes behavioral and cognitive attitudes of the trader at the micro level and explains their effects on his decision making at the macro level. The proposed simulator is composed of heterogeneous Trader agents with a behavioral cognitive model and the CentralMarket agent matching buying and selling orders. Our artificial stock market is implemented using distributed artificial intelligence techniques. The resulting simulation system is a tool able to numerically simulate financial market operations in a realistic way. Experiments show that representing the micro level led us to validate some stylized facts related to stock market and to observe emergent socio-economic phenomena at the macro level.
Zahra Kodia, Lamjed Ben Said,Stylized facts study through a multi-agent based simulation of an artificial stock market
Lecture Notes in Economics and Mathematical Systems, in: Marco Li Calzi & Lucia Milone & Paolo Pellizzari (ed.), Progress in Artificial Economics, pages 27-38, Springer., 2010
Abstract
This paper explores the dynamics of stock market from a psychological perspective using a multi-agent simulation model. We study the stock market trading behavior and the interactions between traders. We propose a novel model which includes behavioral and cognitive attitudes of the trader at the micro level and explains their effects on his decision making at the macro level. The proposed simulator is composed of heterogeneous Trader agents with a behavioral cognitive model and the CentralMarket agent matching buying and selling orders. Simulation experiments are being performed to observe stylized facts of the financial times series and to show that the psychological attitudes have many consequences on the stock market dynamics. These experiments show that the modelization of the micro level led us to observe emergent socio-economic phenomena at the macro level.
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2009Zahra Kodia, Lamjed Ben Said
Multi-agent Simulation of Investor Cognitive Behavior in Stock Market
7th International Conference on PAAMS'09, AISC 55, pp.90-99, Salamanca, Spain. Springer Berlin / Heidelberg; ISSN: 1615-3871, 2009
Abstract
In this paper, we introduce a new model of Investor cognitive behavior in stock market. This model describes the behavioral and cognitive attitudes of the Investor at the micro level and explains their effects on his decision making. A theoretical framework is discussed in order to integrate a set of multidisciplinary concepts. A Multi-Agent Based Simulation (MABS) is used to: (1) validate our model, (2) build an artificial stock market: SiSMar and (3) study the emergence of certain phenomena relative to the stock market dynamics at the macro level. The proposed simulator is composed of heterogeneous Investor agents with a behavioral cognitive model, an Intermediary agent and the CentralMarket agent matching buying and selling orders. Our artificial stock market is implemented using distributed artificial intelligence techniques. The resulting simulator is a tool able to numerically simulate financial market operations in a realistic way. Preliminary results show that representing the micro level led us to build the stock market dynamics, and to observe emergent socio-economic phenomena at the macro level.
Wassim Ayadi, ,A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data
BioData mining Volume 2 Numéro 1, 2009
Abstract
Background
In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed.
Methods
We introduce BiMine, a new enumeration algorithm for biclustering of DNA microarray data. The proposed algorithm is based on three original features. First, BiMine relies on a new evaluation function called Average Spearman’s rho (ASR). Second, BiMine uses a new tree structure, called Bicluster Enumeration Tree (BET), to represent the different biclusters discovered during the enumeration process. Third, to avoid the combinatorial explosion of the search tree, BiMine introduces a parametric rule that allows the enumeration process to cut tree branches that cannot lead to good biclusters.
Results
The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data. The experimental results show that BiMine competes well with several other biclustering methods. Moreover, we test the biological significance using a gene annotation web-tool to show that our proposed method is able to produce biologically relevant biclusters. The software is available upon request from the authors to academic users.
, Lamjed Ben Said,Evolutionary optimization of the multiobjective transshipment problem with limited storage capacity
In Winter Simulation Conference (pp. 2375-2383)., 2009
Abstract
In situations where some sellers have surplus stock while others, belonging to the same firm, are stocked out, it may be desirable to share the unsold units to fulfill more unmet demands and avoid holding costs. Such practice is named Transshipment. It ensures cost reduction and service level improvement. In this paper, we present a multiobjective study of a multi-location transshipment inventory which optimizes three objectives: (1) the aggregate cost, (2) the fill rate, and (3) the shared inventory quantity (SIQ), in the presence of different storage capacity constraints. Simulation is needed to evaluate the expected value of the problem stochastic objective functions. Two reference evolutionary multiobjective algorithms (SPEA2 and NSGA-II) are used to solve instances of the problem. Based on the obtained Pareto fronts, it is shown that both low aggregate cost and high fill rate levels could be ensured, while the shared inventory quantity is considerably increased.
Mohamed Hmiden, Lamjed Ben Said,Transshipment problem with uncertain customer demands and transfer lead time
In 2009 International Conference on Computers & Industrial Engineering (pp. 476-481). IEEE., 2009
Abstract
This paper deals with the transshipment problem characterized by the uncertainty relative to customer demands and transfer lead time. We consider a distribution network of one supplier and N locations selling an innovative product. The customer demands and the transfer lead time are evaluated based on expert judgments and they are consequently represented by fuzzy sets. Our aims in this work are: (1) to identify a transshipment policy that takes into account the fuzziness of customer demands and transfer lead times and (2) to determine the approximate replenishment quantities which minimize the total inventory cost. In order to achieve these aims, we propose a new transshipment policy where the transshipment decision is made within the period and the possible transshipment decision moments belong to a fuzzy set. We consider the decision maker behavior types (pessimistic and optimistic) to determine the precise transshipment decision moment and the transshipment quantity. We propose a hybrid algorithm based on fuzzy simulation and genetic algorithm to approximate the optimal replenishment quantities.
