Click the above “Beginner Learning Vision“, select “Star” or “Top“ Heavyweight content delivered first-hand Paper Author | Li Chen Editor | Heart of Autonomous Driving This year’s CVPR Best Paper was awarded to end-to-end autonomous driving, which, in the eyes of automotive professionals, represents a consensus: end-to-end autonomous driving is the future of the industry. … Read more
01 Reinforcement Learning (RL), also known as evaluative learning or enhanced learning, is one of the paradigms and methodologies in machine learning used to describe and solve the problem of agents learning strategies to maximize rewards or achieve specific goals through interactions with the environment. It is inspired by the behaviorist theory in psychology, which … Read more
Introduction Language Agents, which are intelligent agents based on large language model technology, have great potential for general artificial intelligence (AGI) and large-scale automation of existing human labor if deployed responsibly. They may usher in a new era of scalable artificial intelligence and human collaboration. However, like all new technologies, we must also pay attention … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering audiences including NLP graduate students, university professors, and corporate researchers. The Vision of the Community is to promote communication and progress between the academia and industry of natural language processing and machine learning, especially for the advancement of … Read more
Keywords: Microrobots, Biomedical Engineering, Reinforcement Learning Paper Title: Autonomous 3D positional control of a magnetic microrobot using reinforcement learning Journal: Nature Machine Intelligence Paper Link: https://www.nature.com/articles/s42256-023-00779-2 The small size of microrobots allows them to access all parts of the body, facilitating targeted treatment and diagnosis. Recent studies have revealed the enormous potential of microrobots in … Read more
“Hyperparameter optimization is a key step in the development of deep reinforcement learning algorithms, aimed at improving performance by adjusting the algorithm’s hyperparameters. Currently, there are various hyperparameter optimization methods, among which Bayesian optimization is widely used due to its efficiency and intelligent search mechanism. Therefore, this article mainly studies hyperparameter optimization methods based on … Read more
New Intelligence Compilation Source: arxiv Editor: Xiao Qin 【New Intelligence Guide】Traditional memory architectures struggle with relational reasoning. This paper from DeepMind and University College London proposes the Relational Memory Core (RMC), which can perform relational reasoning within sequential information, achieving state-of-the-art performance on the WikiText-103, Project Gutenberg, and GigaWord datasets. Paper: https://arxiv.org/pdf/1806.01822v1.pdf Memory-based neural networks … Read more