882 resultados para agent-based simulation


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The behaviours of autonomous agents may deviate from those deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, and may be encoded in electronic contracts in order to specify the obliged, permitted and prohibited behaviours of agents that are signatories to such contracts. Enactment and management of electronic contracts thus enables the use of regulatory mechanisms to ensure that agent behaviours comply with the encoded norms. To facilitate such mechanisms requires monitoring in order to detect and explain violation of norms. In this paper we propose a framework for monitoring that is to be implemented and integrated into a suite of contract enactment and management tools. The framework adopts a non-intrusive approach to monitoring, whereby the states of a contract with respect to its contained norms can be inferred on the basis of messages exchanged. Specifically, the framework deploys agents that observe messages sent between contract signatories, where these messages correspond to agent behaviours and therefore indicate whether norms are, or are in danger of, being violated.

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The behaviours of autonomous agents may deviate from those deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent's behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper we propose a generic architecture for observation of agent behaviours, and recognition of these behaviours as constituting, or counting as, compliance or violation. The architecture deploys monitors that receive inputs from observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation and deployment of monitors in electronic contracting environments.

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The behaviours of autonomous agents may deviate from those deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent’s behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper we propose a generic architecture for observation of agent behaviours, and recognition of these behaviours as constituting, or counting as, compliance or violation. The architecture deploys monitors that receive inputs from observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation and deployment of monitors in electronic contracting environments.

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Patient recruitment for clinical trials is expensive and has been a significant challenge, with many trials not achieving their recruitment goals. One method that shows promise for improving recruitment is the use of interactive prompts that inform practitioners of patient eligibility for clinical trials during consultation. This paper presents the ePCRN-IDEA recruitment system, which utilises an agent-based infrastructure to enable real-time recruitment of patients. In essence, whenever patients enter a clinic, the system compares their details against eligibility criteria, which define the requirements of active clinical trials. If a patient is found to be eligible, a prompt is raised to notify the user. In this way, it becomes possible for recruitment to take place quickly in a cost effective manner, whilst maintaining patient trust through the involvement of their own health care practitioner.

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Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.

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In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income. (c) 2005 Elsevier B.V. All rights reserved.

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The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Wireless LAN technology, despite the numerous advantages it has over competing technologies, has not seen widespread deployment. A primary reason for markets not adopting this technology is its failure to provide adequate security. Data that is sent over wireless links can be compromised with utmost ease. In this project, we propose a distributed agent based intrusion detection and response system for wireless LANs that can detect unauthorized wireless elements like access points, wireless clients that are in promiscuous mode etc. The system reacts to intrusions by either notifying the concerned personnel, in case of rogue access points and promiscuous nodes, or by blocking unauthorized users from accessing the network resources.

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Wireless LANs are growing rapidly and security has always been a concern. We have implemented a hybrid system, which will not only detect active attacks like identity theft causing denial of service attacks, but will also detect the usage of access point discovery tools. The system responds in real time by sending out an alert to the network administrator.

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ACR is supported by a research grant from CNPq.

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L'obiettivo della tesi è proporre e motivare l'adozione di un modello computazionale Agent-Based nell'ambito del Self-Management di malattie croniche in un sistema di mobile Health. Viene quindi affrontata in maniera approfondita la tematica del mobile Health, settore in grande espansione che vede l'introduzione massiccia dei dispositivi mobili (smartphone, tablet, PDA) in ambito sanitario, e quella del Self-Managment di malattie croniche, un processo di cura caratterizzato dalla partecipazione autonoma del paziente stesso, fornendo una panoramica dei vari approcci computazionali sviluppati. Successivamente vengono presentate le peculiarità dei modelli computazionali risultati dalle ricerche in letteratura strumenti innovati nell'ambito. Nel caso di studio viene adottata la tecnica di modellazione Agent-Based per sviluppare un modello a supporto di malati cronici affetti da diabete mellito di tipo 1. Con la successiva implementazione sulla piattaforma di simulazione MASON, vengono eseguiti diversi esperimenti per dimostrare la fattibilità dell’approccio adottato nell'ambito del Self-Management di malattie croniche.