Reinforcement Learning

CMU Researcher Uses Deep Reinforcement Learning to help Control Nuclear Fusion Reactions

AI Paper Summary
The process of joining two hydrogen nuclei to create a single, heavier nucleus is known as nuclear fusion. Massive amounts of energy are released...

Microsoft Researchers Develop a Game Theoretic Approach to Provably Correct and Scalable Offline Reinforcement Learning

AI Paper Summary
Even though Machine learning is used in most fields and aspects, most of the automation is designed by humans, not artificial intelligence. For example,...

Researchers from South Korea Propose a Machine Learning Model that Adjusts Video Game Difficulty based on Player Emotions

AI Paper Summary
Dynamic difficulty adjustment (DDA) is a technique for automatically altering a game's features, behaviors, and scenarios in real-time based on the player's proficiency so...

In Latest Machine Learning Research, A Group at CMU Release a Simple and Efficient Implementation of Recurrent Model-Free Reinforcement Learning (RL) for Future Work...

AI Paper Summary
Most real-world situations involve noise and incomplete information, unlike decision-making algorithms, which often concentrate on simple problems where most information is already available. To...

Researchers At Seoul National University Developed A Deep Learning Framework To Improve A Robotic Sketching Agent’s Skills

AI Paper Summary
This article's primary research objective was to develop something cool with non-rule-based techniques such as deep learning; they believed drawing is cool to display...

Amazon AI Introduces ‘PAVE’: A Novel Reinforcement Learning Model That Uses Lazy-MDP Formalism To Improve Recall of Product Attribute Extraction Models

AI Paper Summary
Millions of products are available in e-commerce stores' catalogs. A significant portion of these products is listed by independent vendors. There are often errors...

Researchers at The University of Luxembourg Develop a Method to Learn Grasping Objects on the Moon from 3D Octree Observations with Deep Reinforcement Learning

AI Shorts
The goal of planetary exploration is to improve science by revealing new information about the geology and resource potential of other worlds. Extraterrestrial robotic...

Researchers From Princeton And Max Planck Developed A Reinforcement Learning–Based Simulation That Shows The Human Desire Always To Want More May Have Evolved As...

AI Paper Summary
Through the means of a computational framework of reinforcement learning, researchers from Princeton University have tried to find the relationship between happiness with habituation...

Researchers from DeepMind and University College London Propose Stochastic MuZero for Stochastic Model Learning

AI Paper Summary
Recent research has shown that model-based reinforcement learning is incredibly effective. However, learning a model separately from using it during planning can be challenging...

Nvidia AI Research Team Presents A Deep Reinforcement Learning (RL) Based Approach To Create Smaller And Faster Circuits

AI Paper Summary
There is a law known as Moore's law, which states that the number of transistors on a microchip doubles every two years. And as...

UC Berkeley and Google AI Researchers Introduce ‘Director’: a Reinforcement Learning Agent that Learns Hierarchical Behaviors from Pixels by Planning in the Latent Space...

AI Paper Summary
UC Berkeley and Google AI Researchers Introduce 'Director': a Reinforcement Learning Agent that Learns Hierarchical Behaviors from Pixels by Planning in the Latent Space...

Deepmind AI Researchers Introduce ‘DeepNash’, An Autonomous Agent Trained With Model-Free Multiagent Reinforcement Learning That Learns To Play The Game Of Stratego At Expert...

AI Paper Summary
For several years, the Stratego board game has been regarded as one of the most promising areas of research in Artificial Intelligence. Stratego is...
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