14 research outputs found
CARI'96 : actes du 3ème colloque africain sur la recherche en informatique = CARI'96 : proceedings of the 3rd African conference on research in computer science
No full textCet article présente quelques solutions ayant pour but d'améliorer la testabilité des circuits combinatoires testés de manière pseudo-aléatoire. S'inscrivant dans l'approche Force-Observe, les solutions préconisées consistent en la modification des circuits par l'insertion de deux types de points de test : les points d'observation et les points de contrôle. (Résumé d'auteur
Multi-agent financial market simulation: Evolutionist approach
No full textInternational audienceMulti-agent financial market simulation: Evolutionist approac
Interbank Payment System (RTGS) Simulation Using a Multi-agent Approach
No full textInternational audienceThis work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity provided in the system on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents reasoning is based on a repeated aggregate game of over several payment days where each bank plays against the other banks. For adaptive behaviour we integrate into bank agents a learning classifier system. We carry out then several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to be answered is: what are the cash amounts that banks must provide and under what constraints (costs of liquidity and delaying) the system beyond the lack of liquidity (illiquidity)? We find that liquidity e volution depends on costs coefficients
Interbank Payment System (RTGS) Simulation Using a Multi-agent Approach
No full textInternational audienceThis work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity provided in the system on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents reasoning is based on a repeated aggregate game of over several payment days where each bank plays against the other banks. For adaptive behaviour we integrate into bank agents a learning classifier system. We carry out then several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to be answered is: what are the cash amounts that banks must provide and under what constraints (costs of liquidity and delaying) the system beyond the lack of liquidity (illiquidity)? We find that liquidity e volution depends on costs coefficients
Multi-agent financial market simulation: Evolutionist approach
No full textInternational audienceMulti-agent financial market simulation: Evolutionist approac
Multi-agent financial market simulation: Evolutionist approach
No full textInternational audienceMulti-agent financial market simulation: Evolutionist approac
Interbank Payment System (RTGS) Simulation Using a Multi-agent Approach
No full textInternational audienceThis work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity provided in the system on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents reasoning is based on a repeated aggregate game of over several payment days where each bank plays against the other banks. For adaptive behaviour we integrate into bank agents a learning classifier system. We carry out then several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to be answered is: what are the cash amounts that banks must provide and under what constraints (costs of liquidity and delaying) the system beyond the lack of liquidity (illiquidity)? We find that liquidity e volution depends on costs coefficients
Interbank Payment System (RTGS) Simulation Using a Multi-agent Approach
No full textInternational audienceThis work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity provided in the system on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents reasoning is based on a repeated aggregate game of over several payment days where each bank plays against the other banks. For adaptive behaviour we integrate into bank agents a learning classifier system. We carry out then several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to be answered is: what are the cash amounts that banks must provide and under what constraints (costs of liquidity and delaying) the system beyond the lack of liquidity (illiquidity)? We find that liquidity e volution depends on costs coefficients
Multi-agent liquidity risk management in an interbank net settlement system
No full textInternational audienceA net settlement system is a payment system between banks, where a large number of transactions are accumulated, usually waiting until the end of each day to be settled through payment instruments like: wire transfers, direct debits, cheques, .... These systems also provide clearing functions to reduce interbank payments but are sometimes exposed to liquidity risks. Monitoring, and optimizing the interbank exchanges through suitable tools is useful for the proper functioning of these systems. The goal is to add to these systems an intelligent software layer integrated with the existing system for the improvement of transactions processing and consequently avoid deadlock situations, deficiencies and improve system efficiency. We model and develop by multi-agent an intelligent tracking system of the interbank exchanged transactions to optimize payments settlement and minimize liquidity risks
