Titlebook: Applied Cognitive Science and Technology; Implications of Inte Sumitava Mukherjee,Varun Dutt,Narayanan Srinivasan Book 2023 The Editor(s) (

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Engineered Ferrites and Their Applications with patents, other resources, or their combination as compared to no stimulation yields concepts of higher quality, (e) when the analogical distance between patents and problem domains decreases, quality increases but novelty decreases.

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Cognitive Effects of the Anthropomorphization of Artificial Agents in Human–Agent Interactionsse for artificial agents, whose intelligence can be implemented independently of morphology. In this chapter, we will review the cognitive and behavioral effects of anthropomorphization such as prosocial behavior, empathy, and altruism, as well as changes in subjective experience that can occur when

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Psychological Factors Impacting Adoption of Decision Support Toolseadiness for psychological acceptance. Ethics and culpability are also potential issues when providing tools in support of decision-making. Consideration of these factors as part of system design will improve adoption and more seamlessly integrate the human-in-the-loop.

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Model-Based Operator Assistance: How to Match Engineering Models with Humans’ Cognitive Representatiopportunity for matching the two. We argue that such matching cannot be performed algorithmically. If humans are to be responsible for the matching, this presupposes that models are equipped with understandable descriptions of their capabilities. Accordingly, we argue that model descriptions are a c

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Behavioral Game Theory in Cyber Security: The Influence of Interdependent Information’s Availabilityons, the network was randomly in a non-susceptible (.) state or a susceptible (.) state with each state occurring 50% of the time. The strike proportions were similar in . and . states and similar in AV and Non-AV conditions. However, the patch proportions were lesser in the Non-AV condition than th

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Computer Vision Technology: Do Deep Neural Networks Model Nonlinear Compositionality in the Brain’s ons and DNN features. Our results suggest that we can infer the selectivity of these regions for particular kinds of visual stimuli using DNN representations of the same stimuli as an intermediary. We also map features from the DNN to individual voxels in the brain regions, thus linking the DNN repr

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Assessment of Various Deep Reinforcement Learning Techniques in Complex Virtual Search-and-Retrieve to the search-and-retrieve missions. The task requires an agent (whether human or model) to traverse an environment and gather target objects while sidestepping distractor objects. The results of the study exhibit that humans accomplished better in training scenarios, whereas model agents performed

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