Volkan Ustun

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Recent interest in distributed vector representations for words has resulted in an increased diversity of approaches, each with strengths and weaknesses. We demonstrate how diverse vector representations may be inexpensively composed into hybrid representations, effectively leveraging strengths of individual components, as evidenced by substantial(More)
Mental simulation is proposed by cognitive psychologists as a candidate to model the human reasoning process. In this paper, we propose a methodology that models mental simulation to create realistic human behavior in simulated environments. This methodology is used to generate realistic intruder and guard behavior in physical security systems simulation.(More)
A first step is taken towards incorporating emotional processing into Sigma, a cognitive architecture that is grounded in graphical models, with the addition of appraisal variables for expectedness and desirability plus their initial implications for attention at two levels of the control hierarchy. The results leverage many of Sigma’s existing capabilities(More)
The successful practice of simulation requires a number of capabilities; two key capabilities are creating a conceptual model of the system to be simulated, and translating the conceptual model to a computational process or simulation program. We describe how OMG's new graphical systems modeling language, OMG SysML#8482; (OMG 2009), can be used to create a(More)
Recently reported results with distributed-vector word representations in natural language processing make them appealing for incorporation into a general cognitive architecture like Sigma. This paper describes a new algorithm for learning such word representations from large, shallow information resources, and how this algorithm can be implemented via(More)
The aim of this paper is twofold: First, to propose a data model that enables the user to model a physical facility at different levels of detail and explicitly incorporate interactions among the components of the facility. Second to suggest a methodology for line-of-sight, which is the primary factor in recognition of threats in physical security settings.
Symbolic architectures are effective at complex cognitive reasoning, but typically are incapable of important forms of sub-cognitive processing – such as perception – without distinct modules connected to them via low-bandwidth interfaces. Neural architectures, in contrast, may be quite effective at the latter, but typically struggle with the former. Sigma(More)