Analogue engineering still relies heavily on manual intervention, but that is changing with the growing use of AI/ML.

University of Pennsylvania researchers tweaked an AI tutor to tailor the difficulty of practice problems for each student.

Abstract: On-policy reinforcement learning (RL) algorithms have demonstrated great potential in robotic control, where effective exploration is crucial for efficient and high-quality policy learning.

Thinking about learning Python coding online? It’s a solid choice. Python is pretty straightforward to pick up, and you can do a lot with it. Whether you’re just curious or looking to build something ...

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.

An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments ...

Abstract: Deep Reinforcement Learning (DRL) is becoming a prominent method for autonomous driving due to its strong capability to generate complex driving policy. However, DRL motion planning still ...