Netlogo simulation: effective for agent based modeling in artificial intelligence

Today practical knowledge is as important as theretical knowledge. But the cost of setting up practical l abs is not easy and needs maintenance on a regular basis. But with the emergence of many simulators, practical knowledge can be imparted throug h setting up of virtual laboratories with the help of computers. The cost of maintenance also decreases to alarge extend. Our paper focuses on one such simulator named NETLOGO. NETLOGO is immergingsimulation software for agent based modeling. Itis easilyinstallable in a machine and can be downloaded from the net. It is free software. This paper deals with the usage of NETLOGO from both student and professors perspectives. The paper will state the advantages and disadvantages of the simulator along with a simulation example. Though there are many agent based programming l anguages yet our paper is trying to show the effectiveness of using NETLOGO as asimulator for agent based modeling

Building agent-based hybrid intelligent systems : a case study

Many complex problems (e.g., financial investment planning, foreign exchange trading, data mining from large/multiple databases) require hybrid intelligent systems that integrate many intelligent techniques (e.g., fuzzy logic, neural networks, and genetic algorithms). However, hybrid intelligent systems are difficult to develop because they have a large number of parts or components that have many interactions. On the other hand, agents offer a new and often more appropriate route to the development of complex systems, especially in open and dynamic environments. Thus, this paper discusses the development of an agent-based hybrid intelligent system for financial investment planning, in which a great number of heterogeneous computing techniques/packages are easily integrated into a unifying agent framework. This shows that agent technology can indeed facilitate the development of hybrid intelligent systems.<br /

Modélisation multimodèle des réseaux dynamiques : cas des réseaux pair-à-pair

National audienceDans cet article, nous présentons une démarche conceptuelle liant des modélisations issues des mondes pair-à-pair et multi-agents afin de prendre en compte le comportement de l'utilisateur dans la modélisation et la simulation des réseaux pair-à-pair. Nous présentons aussi un outil de simulation que nous avons adapté ainsi que nos premiers résultats qui indiquent que cette démarche est cohérente

Performance Modelling, and Adaptive Control for Linked Sequential Systems

This thesis investigates the dynamics of linked sequential systems of machines in industrial laundries. Two aspects are considered: firstly the control of such systems and in particular the decision making point when a batch to be processed can be sent to one of many identical machines, and secondly the modelling of the whole system of linked machines. The decision making point in the control of these systems is frequently implemented in a sub-optimal manner, or a manner which becomes sub-optimal as conditions change. An adaptive system is preferable and an Evolutionary Artificial Neural Network approach (EANN) is proposed. The EANN is tested on simulations of real laundry systems and shown to be effective. Then it is applied to two abstract game playing problems in order to better understand its limitations. Limitations are found to include the fact that if learning does not appear to take place, it is not possible to determine if this is a failure of the Evolutionary approach or the Artificial Neural Network parameters. The dynamics and performance of Linked Sequential Systems in Industrial Laundries are not well understood or covered by theory in the literature. The theory of the performance of these systems is outlined, and an Agent Based Model (ABM) simulation presented. The ABM simulation is explained and then the simulation is compared to a real world system in an existing laundry. The performance of the existing system is measured and compared to the prediction of the ABM simulation. The ABM simulation is shown to offer a better understanding of the system than the previous static calculation. Finally the ABM is used in a design exercise to show how it could be used to specify a system more accurately than the static calculation at design stage

Model-driven engineering techniques for the development of multi-agent systems

Model-driven engineering (MDE), implicitly based upon meta-model principles, is gaining more and more attention in software systems due to its inherent benefits. Its use normally improves the quality of the developed systems in terms of productivity, portability, inter-operability and maintenance. Therefore, its exploitation for the development of multi-agent systems (MAS) emerges in a natural way. In this paper, agent-oriented software development (AOSD) and MDE paradigms are fully integrated for the development of MAS. Meta-modeling techniques are explicitly used to speed up several phases of the process. The Prometheus methodology is used for the purpose of validating the proposal. The meta-object facility (MOF) architecture is used as a guideline for developing a MAS editor according to the language provided by Prometheus methodology. Firstly, an Ecore meta-model for Prometheus language is developed. Ecore is a powerful tool for designing model-driven architectures (MDA). Next, facilities provided by the Graphical Modeling Framework (GMF) are used to generate the graphical editor. It offers support to develop agent models conform to the meta-model specified. Afterwards, it is also described how an agent code generator can be developed. In this way, code is automatically generated using as input the model specified with the graphical editor. A case of study validates the method put in practice for the development of a multi-agent surveillance system

Eastern European Political Cultures: Modeling Studies

This collective volume introduces ten European authors and their researches on political culture modeling. They share the interest for the political methodology, on the one hand, and for the political culture of the Eastern European post-communist regimes and their transition to democracy, on the other hand. Their research papers have been peer-reviewed and accepted as papers of the 2nd edition of the European Conference on Political Attitudes and Mentalities, ECPAM’2013, organized as a virtual conference by the European Research Group on Political Attitudes and Mentalities, EPAM, on November 8th, 2013. The main theme of the conference has provided the subject of this collective volume: “Political Attitudes and Political Cultures: Theoretical, Analytical, Computational and Simulation Models”