797 resultados para Agent-based model
Resumo:
Users are facing an increasing challenge of managing information and being available anytime anywhere, as the web exponentially grows. As a consequence, assisting them in their routine tasks has become a relevant issue to be addressed. In this paper, we introduce a software framework that supports the development of Personal Assistance Software (PAS). It relies on the idea of exposing a high level user model in order to increase user trust in the task delegation process as well as empowering them to manage it. The framework provides a synchronization mechanism that is responsible for dynamically adapting an underlying BDI agent-based running implementation in order to keep this high-level view of user customizations consistent with it.
Resumo:
Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.
Resumo:
Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.
Resumo:
Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision.
Resumo:
This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.
Resumo:
A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.
Resumo:
Sophisticated models of human social behaviour are fast becoming highly desirable in an increasingly complex and interrelated world. Here, we propose that rather than taking established theories from the physical sciences and naively mapping them into the social world, the advanced concepts and theories of social psychology should be taken as a starting point, and used to develop a new modelling methodology. In order to illustrate how such an approach might be carried out, we attempt to model the low elaboration attitude changes of a society of agents in an evolving social context. We propose a geometric model of an agent in context, where individual agent attitudes are seen to self-organise to form ideologies, which then serve to guide further agent-based attitude changes. A computational implementation of the model is shown to exhibit a number of interesting phenomena, including a tendency for a measure of the entropy in the system to decrease, and a potential for externally guiding a population of agents towards a new desired ideology.
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The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.
Resumo:
A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.
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This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.
Resumo:
Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.
Resumo:
NK model, proposed by Kauffman (1993), is a strong simulation framework to study competing dynamics. It has been applied in some social science fields, for instance, organization science. However, like many other simulation methods, NK model has not received much attention from Management Information Systems (MIS) discipline. This tutorial, thus, is trying to introduce NK model in a simple way and encourage related studies. To demonstrate how NK model works, this tutorial reproduces several Levinthal’s (1997) experiments. Besides, this tutorial attempts to make clear the relevance between NK model and agent-based modeling (ABM). The relevance can be a theoretical basis to further develop NK model framework for other research scenarios. For example, this tutorial provides an NK model solution to study IT value cocreation process by extending network structure and agent interactions.
Resumo:
The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission, and one logical layer for element communication. A simple case study is presented to analyse the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.
Resumo:
Chemical-looping combustion (CLC) has the inherent property of separating the product CO2 from flue gases. Instead of air, it uses an oxygen carrier, usually in the form of a metal oxide, to provide oxygen for combustion. All techniques so far proposed for chemical looping with solid fuels involve initially the gasification of the solid fuel in order for the gaseous products to react with the oxygen carrier. Here, the rates of gasification of coal were compared when gasification was undertaken in a fluidised bed of either (i) an active Fe-based oxygen carrier used for chemical looping or (ii) inert sand. This enabled an examination of the ability of chemical looping materials to enhance the rate of gasification of solid fuels. Batch gasification and chemical-looping combustion experiments with a German lignite and its char are reported, using an electrically-heated fluidised bed reactor at temperatures from 1073 to 1223 K. The fluidising gas was CO2 in nitrogen. The kinetics of the gasification were found to be significantly faster in the presence of the oxygen carrier, especially at temperatures above 1123 K. A numerical model was developed to account for external and internal mass transfer and for the effect of the looping agent. The model also included the effects of the evolution of the pore structure at different conversions. The presence of Fe2O3 led to an increase in the rate of gasification because of the rapid oxidation of CO by the oxygen carrier to CO2. This resulted in the removal of CO and maintained a higher mole fraction of CO2 in the mixture of gas around the particle of char, i.e. within the mass transfer boundary layer surrounding the particle. This effect was most prominent at about 20% conversion when (i) the surface area for reaction was at its maximum and (ii) because of the accompanying increase in porosity and pore size, intraparticle resistance to gas mass transfer within the particle of char had fallen, compared with that in the initial particle. Excellent agreement was observed between the rates predicted by the numerical model and those observed experimentally. ©2013 Elsevier Ltd. All rights reserved.