June 23, 2022, 5:07 p.m. | Aneesh Tickoo

MarkTechPost www.marktechpost.com

Reinforcement learning (RL) requires exploration of the environment. Exploration is even more critical when extrinsic incentives are few or difficult to obtain. Due to the massive size of the environment, it is impractical to visit every location in rich settings due to the range of helpful exploration paths. Consequently, the question is: how can an […]


The post 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 appeared first …

ai paper summary ai shorts algorithm applications artificial intelligence country deepmind editors pick exploration learning machine learning observable power reinforcement learning researchers self-supervised learning staff supervised learning tech news technology uk unicorns

More from www.marktechpost.com / MarkTechPost

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Social Insights & Data Analyst (Freelance)

@ Media.Monks | Jakarta

Cloud Data Engineer

@ Arkatechture | Portland, ME, USA