We present in this paper a generic methodology based on genetic automata for modelling community detection. With Communities, we deal with dynamic organizations which are self-organized from two aspects, the spatial one and the functional one. We propose in this paper a general methodology which extends cellular based modelling like Schelling models to more sophisticated approaches based on age...

Auction-based prices have been used in multi-agent simulations for a long time. Currently, dynamic simulations of transport in logistics networks are usually performed while prices are given as input parameters. A model where such transport logistic simulations are based on auction-based prices has been studied in some detail recently, and shows interesting dynamic properties. The model conside...

Massive multi-agent systems with emergent global behavior represent a new paradigm in designing and building program systems for handling complex problems. Emergence, nonlinearity and self-organization of global behavior underpin robustness, flexibility and autonomy of massive multi-agent systems. On the other hand, this makes the traditional design approach difficult, if not impossible. In thi...

Artificially intelligent agents are enjoying increased adoption in both the video game and simulation industry - being used for training education as well entertainment purposes with largescale real-time strategy games. Both type of systems have a need large numbers units. While traditional scalability solutions (e.g. segmenting terrain using separate hardware to process various sections) can b...

Autonomic computing is a computing system that can manage itself by self-configuration, self-healing, self-optimizing and self-protection. Researchers have been emphasizing the strong role that multi agent systems can play progressively towards the design and implementation of complex autonomic systems. The important of autonomic computing is to create computing systems capable of managing them...

Current business trends, policy markets, production requirements, etc., have created the need for integrating Multi Agent Systems (MAS). In the agent-specialized literature, we have found very little work about MAS methodologies that allow us to build MAS which is made up of two or more MASs. We think that several difficult challenges for automated systems can be tackled by giving full meaning ...

Numerous works aim to design agents and multi-agent systems architectures in order to enable cooperation and coordination between agents. Most of them use organizational structures or societies metaphor to define the MAS architecture. It seems improbable that a rigid unscalable organization could handle a real world problem, so it is interesting to provide agents with abilities to self-organize...

In this paper I ask questions about the evolution of self-organized activity cycles that are found in some ant colonies. I use a computer model that generates periodic activity patterns in interacting subunits and explore the parameters of this model using a genetic algorithm in which selecting on one aspect of the system produces the distinctive self-organized pattern. The general point that I...

Because of complex sensor networks in smart city management, it is very difficult to optimize the data processing from all kinds of sensors. Here a multi-agent system (MAS) is made for data processing and optimization of sensor networks in smart city management. First, the sensor network in smart city management is modeled as a self-organized and decentralized agent swarm. In the MAS, each agen...