David Pietrocola

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Demand is on the rise for scientifically based human-behavior models that can be quickly customized and inserted into immersive training environments to recreate a given society or culture. At the same time, there are no readily available science model-driven environments for this purpose (see survey in Sect. 2). In researching how to overcome this(More)
In this study, we explore dimensions of comparison amongst complex agent-based models. Specifically, we look at holistic models of leaders-in-context. We focus our analysis on alternative models of the same phenomenon, that of the rise and fall of two corporations, respectively. The models were built by students with introductory training on the methodology(More)
The growing interest in immersive 3D environments populated with intelligent agents has led to a flurry of approaches and products with particular focuses, including cultural awareness training, language training, and operations " what-if " scenarios. Human terrain data present challenges that require categorization efforts. We present a taxonomy and(More)
Q is an unmanned ground vehicle designed to compete in the Autonomous and Navigation Challenges of the AUVSI Intelligent Ground Vehicle Competition (IGVC). Built on a base platform of a modified PerMobil Trax off-road wheel chair frame, and running off a Dell Inspiron D820 laptop with an Intel t7400 Core 2 Duo Processor, Q gathers information from a SICK(More)
This paper is dedicated to the " living cognition " issues, which concern the ability of a cognitive model to simulate humans' mental activities when dynamically interacting with the external environment. After having introduced the theoretical foundations of this approach, an integrative COgnitive Simulation MOdel of the DRIVEr is presented (i.e.(More)
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