一种基于移动Agent的抗攻击性IDS模型

随着入侵检测系统(Inhusion Detection System——IDS)性能的逐步提高，攻击者往往在入侵目标网络之前攻击IDS，使其丧失保护功能。在当前常用的分布式入侵检测系统的基础上，提出了一种能够对抗拒绝服务(Denial of Service——DoS)攻击的IDS模型，并指出了将当前的分布式IDS转换成此模型的配置方法。     

An agent-based model of public space use

Computational models have been described as exceptionally adept at examining the complex relationships of human and crowd behaviour, with a significant portion dedicated to investigating spatial behaviour in defined environments. Within this context, this paper presents an agent-based model (ABM) for simulating activity in public spaces at the level of the individual user. Although other ABMs of individuals' spatial activity exist, they are often found to simulate specific building-related activities, and fewer still are found to examine activity in public spaces, in a systematic manner. This research provides a generalized formalization of human spatial behaviour incorporating stationary activities and social interaction within a 3D environment, and is presented using a widely accepted framework for describing ABM, the Overview, Design Concepts, and Details (ODD) protocol. A sample study using a synthetic environment is used to demonstrate applicability, and the model is tested extensively to establish robustness. Furthermore, model output is compared to observed activity patterns in other studies of similar spaces, and simulated spatial patterns of activity are found to match those observed in real-world scenarios, providing insight into the dynamics of the processes, and highlighting the potential of this approach for studying the complexities of human spatial behaviour.     

The garbage can model of organizational choice: An agent-based reconstruction

We reconstruct Cohen, March and Olsen’s original Garbage Can model of organizational choice as a multi-agent system. We show that while some of the original results might be viewed as artifacts of particular modeling choices, the basic insights of the original model are confirmed over a wide range of experimental conditions. The simulation experiments confirm and extend some of the most interesting conclusions of the Garbage Can model: most decisions are made without solving any problem, the few problems that are solved generally pertain to the lower hierarchical levels and, consequently, the members of an organization encounter the same old problems again and again.     

An agent-based approach to tool integration

Tool integration is a very difficult challenge. Problems may arise at different abstraction levels and from several sources such as heterogeneity of manipulated data, incompatible interfaces, or uncoordinated services, to name just a few examples. On the other hand, applications based on the coherent composition of activities, components, services, and data from heterogeneous sources are increasingly present in our everyday lives. Consequently, tool integration takes on increasing significance.In this paper we analyze the tool-integration problem at different abstraction levels and discuss different views on a layered software architecture that we have designed specifically for a middleware that supports the execution of distributed applications for the orchestration of human/system activities. We noticed that the agent paradigm provided a suitable technology for abstraction in tool integration. Throughout the paper, the discussion refers to a case study in the bioinformatics domain.     

An agent-based approach to multisensor coordination

This paper presents an automated system for multiple sensor placement based on the coordinated decisions of independent, intelligent agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Hence, it is necessary to incorporate multiple sensors in order to obtain complete information. The overall goal of the system is to provide the surface coverage necessary to perform feature inspection on one or more target objects in a cluttered scene. This is accomplished by a group of cooperating intelligent sensors. In this system, the sensors are mobile, the target objects are stationary and each agent controls the position of a sensor and has the ability to communicate with other agents in the environment. By communicating desires and intentions, each agent develops a mental model of the other agents' preferences, which is used to avoid or resolve conflict situations. In this paper we utilize cameras as the sensors. The experimental results illustrate the feasibility of the autonomous deployment of the sensors and that this deployment can occur with sufficient accuracy as to allow the inspection task to be performed.     

Exploring the polycentric city with multi-worker households: An agent-based microeconomic model

We propose an agent-based dynamics which leads an urban system to the standard equilibrium of the Alonso, Muth, Mills (AMM) framework. Starting for instance from a random initialization, agents move and bid for land, performing a kind of local search and finally leading the system to equilibrium rent, density and land use. Agreement with continuous analytical results is limited only by the discreteness of simulations. We then study polycentrism in cities with this tool. Two job centers are introduced, and the economic, social and environmental outcomes of various polycentric spatial structures are presented. We also introduce two-worker households whose partners may work in different job centers. When various two-worker households are mixed, polycentrism is desirable, as long as the centers are not too distant from each other. The environmental outcome is also positive, but housing surfaces increase.     

Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card

Smartphone credit card (SCC) is an emerging payment method using NFC-enabled smartphones. The proximity payment allows consumers to pay their products and services by waving their smartphones with a NFC reader. While there are advantageous adopting SCC, the adoption rate has not been encouraging. Interestingly, existing research work on past information technology and system models have so far focused primarily on organizational context and adopted specifically for work. Furthermore, past antecedents were mainly constructed using electronic commerce literatures which do not reflect the actual mobile environment. In contrast SCC is mainly adopted voluntarily by mobile users and for personal purposes. Thus this leads to the difficulty in drawing meaningful conclusion. The study addresses these limitations by proposing a new mobile technology acceptance model (MTAM) which consists of mobile usefulness (MU) and mobile ease of use (MEU) to determine SCC adoption. In anticipating on the complexity which exists in the mobile environment, additional mobile constructs namely mobile perceived security risk (MPSR), mobile perceived trust (MPT), mobile perceived compatibility (MPC) and mobile perceived financial resources (MPFR) were incorporated into the parsimonious MTAM. The integrated model was applied to 459 mobile users through a questionnaire approach and tested using partial least square-structural equation modelling-artificial neural network (PLS-SEM-ANN) has provided a new impact and a possible new research methodology paradigm as it is able to capture both linear and non-linear relationships. While the model confirms the role of MU in MTAM, MEU needs for more attention in practice. The results from the extended model showed that only three of the proposed hypotheses were non-significant in this study and thus warrant further investigation. The study contributes to academia by proposing new mobile constructs that brings together MTAM to assess the likelihood of mobile users to adopt SCC. The study also offers several important managerial implications which can be generalized to the mobile studies of other transportation, hotel, banking, and tourism industries.     

BioWar: scalable agent-based model of bioattacks

While structured by social and institutional networks, disease outbreaks are modulated by physical, economical, technological, communication, health, and governmental infrastructures. To systematically reason about the nature of outbreaks, the potential outcomes of media, prophylaxis, and vaccination campaigns, and the relative value of various early warning devices, social context, and infrastructure, must be considered. Numerical models provide a cost-effective ethical system for reasoning about such events. BioWar, a scalable citywide multiagent network numerical model, is described in this paper. BioWar simulates individuals as agents who are embedded in social, health, and professional networks and tracks the incidence of background and maliciously introduced diseases. In addition to epidemiology, BioWar simulates health-care-seeking behaviors, absenteeism patterns, and pharmaceutical purchases, information useful for syndromic and behavioral surveillance algorithms.     

An accessibility measure for the combined travel demand model

The accessibility-oriented transport planning method is critical for many high population density cities in China. Most definitions of accessibility only consider spatial separation and ignore the influence of traveler choice on accessibility. In this paper, the combined travel demand model is employed in transport planning. The travelers’ choice behavior of the model is based on the random utility theory. The model overcomes inconsistence problem of the sequential four-step model on travel behavior and con...     

An agent-based model for simulating urban crime with improved daily routines

We propose a scalable agent-based crime simulation model based on the routine activity theory. It uses census data and time geography to create a synthetic population with residences and job locations, commuting schedules, and daily routines constrained by disposable time that are more representative than existing models. The time and location of crime incidents in this model are determined by random encounters between vulnerable targets and motivated offenders when they travel or carry out scheduled activities on a road network. This model is applied to simulate robberies in January 2011 for Baton Rouge, Louisiana. Three scenarios are simulated to demonstrate its value for crime theory development and shed light on modeling issues in need of improvement before it can reliably assist policymaking or inform the public. Major findings from this study include the model's ability to replicate prominent robbery hotspots in the study area with various degrees of success and the consistent effects of target definition and offender strategy on model performance. The study also suggests missing model components to effectively constrain the displacement of crime opportunities under hotspot policing, which can be the key to resolving contradiction between our simulation results and other empirical researches and crime simulations.     

An agent-based model to study compliance with safety regulations at an airline ground service organization

According to aviation statistics, most of the safety occurrences happen not in the air, but on the ground. Management of airlines and airports often consider failures to comply with safety-related regulations as important contributors to safety occurrences. To address the issue of compliance, approaches based on external regulation of the employees’ behavior were proposed. Unfortunately, an externally imposed control is often not internalized by employees and has a short-term effect on their performance. To achieve a long-term effect, employees need to be internally motivated to adhere to regulations. To understand the role of motivation for compliance in ground service organizations, in this paper a formal agent-based model is proposed based on theories from social science with a wide empirical support. The model incorporates cognitive, social, and organizational aspects. The model was simulated and partially validated by a case study performed at a real airline ground service organization. The model was able to reproduce behavioral patterns related to compliance of the platform employees in this study. Based on the model, global sensitivity analysis was performed. The results of this analysis together with the simulation results were used to generate recommendations to improve compliance.     

Simulating informal settlement growth in Dar es Salaam, Tanzania: An agent-based housing model

The simulation of the growth of informal settlements can be an essential building block to manage urbanization processes in cities of the developing world. We used agent-based modelling to develop a vector-based, micro-scale housing model to simulate the growth of informal settlements. A prototype of the housing model was implemented for Dar es Salaam, Tanzania. The results show that such a vector-based housing model built on three simple rules of spatial change (infilling, extension and enlargement of existing houses) can successfully simulate the housing pattern of informal settlements growth.     

Endogenous rise and collapse of housing price: An agent-based model of the housing market

On the basis of interviews with local real estate agents, this study develops an agent-based model of housing market to determine the cause of rise and collapse of US housing price during the years immediately preceding the US financial crisis (2007–2009). We study the key factors affecting housing price volatility, such as lenient financing and speculation. The dynamic simulation findings in the study show in concrete terms how lenient lending practices combined with speculation can lead to increased volatility in housing price, including sharp rises immediately followed by collapses. The exploratory work in this study will contribute to the understanding of the causes of housing bubbles and inform policy decisions.     

Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna

Interest in assessing the sustainability of socio-ecological systems of urban areas has increased notably, with additional attention generated due to the fact that half the world's population now lives in cities. Urban areas face both a changing urban population size and increasing sustainability issues in terms of providing good socioeconomic and environmental living conditions. Urban planning has to deal with both challenges. Households play a major role by being affected by urban planning decisions on the one hand and by being responsible – among many other factors – for the environmental performance of a city (e.g. energy use). We here present an agent-based decision model referring to the city of Vienna, the capital of Austria, with a population of about 1.7 million (2.3 million within the metropolitan area, the latter being more than 25% of Austria's total population). Since the early 1990s, after decades of negative population growth, Vienna has been experiencing a steady increase in population, mainly driven by immigration. The aim of the agent-based decision model is to simulate new residential patterns of different household types based on demographic development and migration scenarios. Model results were used to assess spatial patterns of energy use caused by different household types in the four scenarios (1) conventional urban planning, (2) sustainable urban planning, (3) expensive centre and (4) no green area preference. Outcomes show that changes in preferences of households relating to the presence of nearby green areas have the most important impact on the distribution of households across the small-scaled city area. Additionally, the results demonstrate the importance of the distribution of different household types regarding spatial patterns of energy use.     

An agent-based approach to knowledge management in distributed design

The collaboration process among individuals with heterogeneous skills in a distributed virtual environment represents a crucial element of the extended enterprise. In order to achieve global optima in design, there is an increasing need for design teams to establish and maintain cooperative work through effective communication, co-location, coordination and collaboration at the knowledge level. Because of the distributed nature of users and information resources involved in the design process, the need for appropriate knowledge management tools is imperative. This paper proposes an agent-based architecture to support multi-disciplinary design teams that cooperate in a distributed design environment (DDE). Using ontologies and multi-agent systems (MAS), the proposed framework aims to optimise design process operation and management by supporting the dialogue among distributed design actors. Received: February 2005/Accepted: January 2006     

Using model checking to assess the dependability of agent-based systems

Model checking and the problem of analyzing the dependability of complex agent-based systems are well matched. Mathematical models of simple agents are relatively straightforward to specify. We can construct a model of the system as a whole from the models of the individual agents, and we can easily express dependability properties in the logical language used in model checking. However, there's one crucial mismatch: the state spaces of complex systems are many orders of magnitude larger than automated model-checking tools can handle. So, the mathematical models of computing systems that we use in model checking must be much simpler than the systems we are modeling. Yet, the models must contain all the detail that's essential to the dependability analysis we are performing, because omitting relevant detail can invalidate the analysis results. To make model checking of agent-based systems feasible and useful, we must answer two crucial questions. Here we describe our current best answers to these questions and how we've applied them to a real-world problem - assessing the UltraLog system.