In the past, reinforcement learning environments were often isolated, making it difficult for developers to share and reuse training environments across different fields and projects. This ...

To deepen the consumability of reinforcement learning algorithms in enterprise AI, developers require tools for collaborating on these projects and for deploying the resulting models into ...

It can take millions of failures for a reinforcement-learning system to become proficient, so most projects using the technology depend on simulations to speed up the laborious process.

ELEC_ENG 373, 473: Deep Reinforcement Learning from Scratch VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Prior deep learning experience (e.g. ELEC_ENG/COMP_ENG 395/495 Deep Learning Foundations ...

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most ...

Discover how reinforcement learning is transforming quadruped robots like Spot into agile, adaptable tools for real-world applications.

PALO ALTO, California, March 6, 2018 /PRNewswire/ -- Researchers from the University of Warsaw, Google AI and deepsense.ai take on a new reinforcement learning challenge on Cloud TPU hardware ...

Guangzhou Ligong Industrial Co., Ltd. recently announced that its patent for the "Multi-Agent Collaborative Scheduling Method and System Based on Maximum Entropy Reinforcement Learning" has been ...