6,645 research outputs found

    Neutrosophic Logic for Mental Model Elicitation and Analysis

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    Mental models are personal, internal representations of external reality that people use to interact with the world around them. They are useful in multiple situations such as muticriteria decision making, knowledge management, complex system learning and analysis. In this paper a framework for mental models elicitation and analysis based on neutrosophic Logic is presented. An illustrative example is provided to show the applicability of the proposal. The paper ends with conclusion future research directions

    Goldilocks Forgetting in Cross-Situational Learning

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    Given that there is referential uncertainty (noise) when learning words, to what extent can forgetting filter some of that noise out, and be an aid to learning? Using a Cross Situational Learning model we find a U-shaped function of errors indicative of a "Goldilocks" zone of forgetting: an optimum store-loss ratio that is neither too aggressive nor too weak, but just the right amount to produce better learning outcomes. Forgetting acts as a high-pass filter that actively deletes (part of) the referential ambiguity noise, retains intended referents, and effectively amplifies the signal. The model achieves this performance without incorporating any specific cognitive biases of the type proposed in the constraints and principles account, and without any prescribed developmental changes in the underlying learning mechanism. Instead we interpret the model performance as more of a by-product of exposure to input, where the associative strengths in the lexicon grow as a function of linguistic experience in combination with memory limitations. The result adds a mechanistic explanation for the experimental evidence on spaced learning and, more generally, advocates integrating domain-general aspects of cognition, such as memory, into the language acquisition process

    Computational Modeling in Applied Problems: collected papers on econometrics, operations research, game theory and simulation

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    Computational models pervade all branches of the exact sciences and have in recent times also started to prove to be of immense utility in some of the traditionally \u27soft\u27 sciences like ecology, sociology and politics. This volume is a collection of a few cuttingedge research papers on the application of variety of computational models and tools in the analysis, interpretation and solution of vexing real-world problems and issues in economics, management, ecology and global politics by some prolific researchers in the field

    What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

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    Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research
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