The company is betting that simulated environments—not more web data—will be key to training the next generation of AI agents ...

While artificial intelligence is advancing at a rapid rate, the learning resources for artificial intelligence are also ...

Abstract: This article investigates the application of deep reinforcement learning (RL) in the reactive collision avoidance control of an autonomous underwater vehicle (AUV) using multibeam ...

This paper proposes an exploration-efficient deep reinforcement learning with reference (DRLR) policy framework for learning robotics tasks incorporating demonstrations. The DRLR framework is ...

The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.

So, you've binged a few treasure-hunting shows and now you're wondering if your own old detector in the garage can find you a pirate chest. One of the first questions that may pop up in your head ...