Nature

Multi-Agent Reinforcement Learning

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
VentureBeat

Google finds that AI agents learn to cooperate when trained against unpredictable opponents

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — is enough to produce cooperative multi-agent systems that adapt to each ...
InfoWorld

Reinforcement learning comes into AI’s mainstream

One of the most noteworthy artificial intelligence trends in 2018 has been the maturation of reinforcement learning into a mainstream approach for building and training statistical models to do useful ...
InfoWorld

What is deep reinforcement learning: The next step in AI and deep learning

Reinforcement learning is well-suited for autonomous decision-making where supervised learning or unsupervised learning techniques alone can’t do the job Reinforcement learning has traditionally ...
Business Wire

Reinforcement Learning 2020: Applications, Innovations and Growth Opportunities - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "Towards Being Truly Intelligent: Next Wave of AI Technologies (Wave 2 - Reinforcement Learning)" report has been added to ResearchAndMarkets.com's offering. As autonomy ...
VentureBeat

Reinforcement learning competition pushes the boundaries of embodied AI

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Since the early decades of artificial intelligence, humanoid robots have ...
Devdiscourse

AI could transform pandemic strategy by balancing lives, economy and resources

Read more about AI could transform pandemic strategy by balancing lives, economy and resources on Devdiscourse ...
EurekAlert!

A graph reinforcement learning framework for real-time distributed multi-robot task allocation

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
The Next Web

Debunking the mysteries of deep reinforcement learning

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human ...