Reinforcement Learning

Latest CMU Research Improves Reinforcement Learning With Lookahead Policy: Learning Off-Policy...

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Reinforcement learning (RL) is a technique that allows artificial agents to learn new tasks by interacting with their surroundings. Because of their capacity to...
Natural Language Understanding and Natural Language Generation

Amazon Research Introduces Deep Reinforcement Learning For NLU Ranking Tasks

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In recent years, voice-based virtual assistants such as Google Assistant and Amazon Alexa have grown popular. This has presented both potential and challenges for...

UC Berkeley Researchers Introduce the Unsupervised Reinforcement Learning Benchmark (URLB)

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Reinforcement Learning (RL) is a robust AI paradigm for handling various issues, including autonomous vehicle control, digital assistants, and resource allocation, to mention a...

Huawei Research Introduces ‘VMAgent’: A Platform for Exploiting Reinforcement Learning (RL)...

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In games and robotics simulators, reinforcement learning has demonstrated competitive performance. Solving mathematical optimization issues with RL approaches has recently attracted a lot of...

UC Berkeley Research Explains How Self-Supervised Reinforcement Learning Combined With Offline...

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Machine learning (ML) systems have excelled in fields ranging from computer vision to speech recognition and natural language processing. Yet, these systems fall short...

Google Research Release Reinforcement Learning Datasets For Sequential Decision Making

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Most reinforcement learning (RL) and sequential decision-making agents generate training data through a high number of interactions with their environment. While this is done...

Google Highlights How Statistical Uncertainty Of Outcomes Must Be Considered To...

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Reinforcement Learning (RL) is a machine learning technique that allows an agent to learn by trial and error in an interactive environment from its...

Google AI Research Propose A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning

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Reinforcement learning(RL) is a machine learning training method that rewards desired behaviors and punishes undesired ones. RL is a typical approach that finds application...

Facebook AI Introduce ‘SaLinA’: A Lightweight Library To Implement Sequential...

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Deep Learning libraries are great for facilitating the implementation of complex differentiable functions. These functions typically have shapes like f(x) → y, where x...

Facebook AI Releases ‘CompilerGym’: A Library of High-Performance, Easy-to-Use Reinforcement Learning...

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Compilers are essential components of the computing stack because they convert human-written programs into executable binaries. When trying to optimize these programs, however, all...