reinforcement learning
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Humanoid AI Robot: A Member of Our Next-generation Family
Abstract: Humanoid robots represent a swiftly advancing area of study and innovation, seeking to produce robots with traits and abilities resembling those of humans. These robots have diverse uses, such as aiding humans in different activities or exploring dangerous or inaccessible areas. Advancing humanoid robots entails combining cutting-edge technologies, including robotics, natural language processing, computer vision, and artificial intelligence. Combining computer science and engineering, robotics is an interdisciplinary subject of study. …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 20–24 Read article
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Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence
Abstract: This work provides an overview of Reinforcement Learning (RL), an important field of artificial intelligence (AI) aims to provide the long-term benefits by learning a relating with a given environment. It spells out everything, what agents and environments do, to how rewards, states, and behaviours. It spent lot of time on looking the most usable RL algorithms, like DQN, SARSA, and Q-Learning. These studies provide a clear view of RL. …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 17–22 Read article
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Applications of Machine Learning Algorithms in Health Data Science (HDS) for Next Research Directions: A Survey Report
Abstract: At present time, data science is the big trend in computer science. The functioning of this technology is purely based on other advanced technology known as machine learning (ML). Data science and ML are subsets of artificial intelligence (AI). When a process of data science is used in healthcare systems, the new system is known as health data science (HDS). HDS is a branch of data science used to handle …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 16–21 Read article