Animals can learn long sequences of actions required for obtaining reinforcement using associative strategies that minimize or obviate the need for explicit knowledge of the causal relationships of ...
Due to their ability to get playable frame rates out of even relatively weak and old graphics cards, upscaling techniques such as AMD FidelityFX Super Resolution (“FSR”) and Nvidia Deep Learning Super ...
Abstract: Reinforcement learning (RL) is a subset of machine learning that allows intelligent agents to acquire the ability of executing desired actions through interactions with an environment. Its ...
Abstract: Federated learning (FL) is a privacy-preserving machine learning paradigm that enables multiple clients to train a unified model without disclosing their private data. However, ...
[and subsequent follow on work: Experimental Exploration of Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection] "In this work we investigate the automatic ...
People often want what they like, and vice versa. However, the common sense is inconsistent with findings on reward-related disorders. For example, some patients suffering from depression and ...
In the present study, we applied reinforcement learning models that are not classically used in experimental economics to a multistep exchange task of the emergence of money derived from a classic ...
What determines which spatial axis people use to represent time? We investigate effects of writing direction. English, like Mandarin Chinese in mainland China, is written left to right and then top to ...
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