Titlebook: Second International Handbook of Science Education; Barry J. Fraser,Kenneth Tobin,Campbell J. McRobbie Book 2012 Springer Science+Business

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Yew-Jin Leee percentage of noise. Overall, the results revealed comparable navigation performance in the two conditions except for the accuracy (e.g., number of target positions reached), indicating similar assistance derived by the system. However, differences between the two modalities are found by correlati

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Donna King,Stephen M. Ritchievigation stack and as a result, improve navigational performance in crowded environments. We developed six agents with different observation spaces to study the impact of different input on the navigation behavior of the agent. We did extensive evaluations against multiple learning-based and classic

Factual

Rowhea Elmeskyact and Effect of AI on Intelligent Autonomous Systems.” It encompassed discussions on theories, applications, and creative innovations in intelligent autonomous systems, covering topics such as autonomous vehicles, intelligent agents, smart sensors and actuators, smart haptics, human–machine intera

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ons in two different physical contexts with 6 different human test participants. The paper demonstrates the trained Affecta-context framework by verifying the robot’s ability to generalize over the input and to match its behaviors to a previously unvisited physical context.

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Reinders Duit,David F. Treagustctor (SSD) and a learning-based tracker (RE.). Through this, we significantly reduce annotation drifts, and, consequently, the required manual supervision. We validate our approach through annotation experiments using our proposed annotation method and existing baselines on a set of drone video fram

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Uri Zoller,Tami Levy Nahumne learning algorithms, such as supervised learning based on artificial neural networks and Gaussian processes, and reinforcement learning, are discussed. They are applied to configure feedback loops, accelerate global optimizations, and directly synthesize optimal controllers. Authors also demonstr

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Eduardo F. Mortimer,Phil Scott,Charbel N. El-Hanine learning algorithms, such as supervised learning based on artificial neural networks and Gaussian processes, and reinforcement learning, are discussed. They are applied to configure feedback loops, accelerate global optimizations, and directly synthesize optimal controllers. Authors also demonstr