23,588 research outputs found

    Little by little does the trick design and construction of a discrete event agent-based simulation framework

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    Simulation is one of the most widely used techniques in operations research. In the military context, agent-based simulations have been extensively used by defense agencies worldwide. Despite the numerous disadvantages and limitations associated with timestepping, most of the combat-oriented agent-based simulation models are time-step implementations. The Discrete Event Scheduling (DES) paradigm, on the other hand, is free of these disadvantages and limitations. The scope of this thesis is to design and implement a library of reusable software components that will facilitate building combat-oriented agent-based simulation models by extending the Simkit DES toolkit. We describe our design of what an agent-based DES implementation framework should look like. We show that the extensive use of Java interfaces allows the user to implement different models and scenarios without being constrained by pre-built components. We also enhance Simkit's existing Sensing model by introducing a Situational Awareness model and a Behavioral model. Finally, we build a small agent-based model using the component architecture to demonstrate the library's functionality.http://archive.org/details/littlebylittledo109453100Hellenic Air Force author.Approved for public release; distribution is unlimited

    From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

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    Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table

    Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

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    In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach

    GAMES: A new Scenario for Software and Knowledge Reuse

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    Games are a well-known test bed for testing search algorithms and learning methods, and many authors have presented numerous reasons for the research in this area. Nevertheless, they have not received the attention they deserve as software projects. In this paper, we analyze the applicability of software and knowledge reuse in the games domain. In spite of the need to find a good evaluation function, search algorithms and interface design can be said to be the primary concerns. In addition, we will discuss the current state of the main statistical learning methods and how they can be addressed from a software engineering point of view. So, this paper proposes a reliable environment and adequate tools, necessary in order to achieve high levels of reuse in the games domain
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