Reinforcement Learning

Researchers From the Berlin Institute of Technology Introduce a New Model based on Deep Reinforcement Learning That Could Allow Mobile Robots to Follow and Guide...

With the ever-changing technology, we are witnessing advancements in technologies every day. One such advancement has come in the Assistance robots. These are primarily...

UC Berkeley Researchers Use a Dreamer World Model to Train a Variety of Real-World Robots to Learn from Experience

Robots need to learn from experience to solve complex in real-world environments. Deep reinforcement learning has been the most common approach to robot learning...

In A Latest Deep Reinforcement Learning Research, Deepmind AI Team Pursues An Alternative Approach In Which RL Agents Can Utilise Large-Scale Context Sensitive Database...

DeepMind Researchers recently expressed concern about how reinforcement learning (RL) agents might use pertinent information to guide their judgments. They have published a new...

DeepMind Researchers Develop ‘BYOL-Explore’: A Curiosity-Driven Exploration Algorithm That Harnesses The Power Of Self-Supervised Learning To Solve Sparse-Reward Partially-Observable Tasks

Reinforcement learning (RL) requires exploration of the environment. Exploration is even more critical when extrinsic incentives are few or difficult to obtain. Due to...

New MIT Research Suggests That Training An AI Model With Mathematically “Diverse” Teammates Can Improve Its Ability To Collaborate With Other AI It Has...

The prevalence of superhuman artificial intelligence (AI) in competitive games such as chess, Atari, StarCraft II, DotA, and poker is growing. Recent advances in deep...

Researchers at DeepMind Trained a Semi-Parametric Reinforcement Learning RL Architecture to Retrieve and Use Relevant Information from Large Datasets of Experience

In our day-to-day life, humans make a lot of decisions. Flexibly applying prior experiences to a novel scenario is required for effective decision-making. One...

The University of Maryland Researchers Introduce a Novel Method, Called TERP, for Reliable Robot Navigation in Uneven Outdoor Terrains Using Deep Reinforcement Learning (DRL)

This Article is written as a summay by Marktechpost Staff based on the paper 'TERP: Reliable Planning in Uneven Outdoor Environments using Deep Reinforcement...

Salesforce AI Research Enhances Multi-Agent Reinforcement Learning via PyTorch Lightning and WarpDrive

Reinforcement Learning (RL) is a branch of Machine Learning (ML) that studies how intelligent agents should behave in a given situation to maximize a...

Salesforce AI Introduces ‘AI Economist’: A Reinforcement Learning (RL) System That Learns Dynamic Tax Policies To Optimize Equality Along With Productivity In Simulated Economies,...

This Article Is Based On The Research Paper 'The AI Economist: Taxation policy design via two-level deep multiagent reinforcement learning'. All Credit For This...

Microsoft AI Researchers Introduce PPE: A Mathematically Guaranteed Reinforcement learning (RL) Algorithm For Exogenous Noise

This Article Is Based On The Research Paper 'Provable RL with Exogenous Distractors via Multistep Inverse Dynamics' and Microsoft article. All Credit For This...

This South Korea-based AI startup, Nota AI, is revolutionizing the AI space with its proprietary hardware-aware AI optimization platform to automate the development process...

Pitch your startup story at asif@marktechpost.com Thanks to Nota AI for the thought leadership/ Educational article above Please don't forget to join our ML...

Google AI Researchers Propose a Meta-Algorithm, Jump Start Reinforcement Learning, That Uses Prior Policies to Create a Learning Curriculum That Improves Performance

This research summary is based on the paper 'Jump-Start Reinforcement Learning' Please don't forget to join our ML Subreddit In the field of artificial intelligence, reinforcement...

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