(RL) is a type of machine learning where a model learns to make decisions by interacting with an environment. Unlike supervised learning, where the model is provided with labeled data, RL involves ...

and multi-agent reinforcement learning methods. The experimental results were promising. The IPPO method outperformed the other methods in terms of convergence and solution quality. It achieved ...

Having machines learn from experience was once considered a dead end. It’s now critical to artificial intelligence, and work in the field has won two men the highest honor in computer science.

AUSTIN, TX AND ROUND ROCK, TX / ACCESS Newswire / March 19, 2025 / Venkata Sai Swaroop Reddy's groundbreaking IEEE research ...

Two trailblazing computer scientists have won the 2024 Turing Award for their work in reinforcement learning, a discipline in ...

Research team developed CLAP, an RL agent for automated penetration testing. It features a coverage mechanism and Chebyshev decomposition critic, reducing attack operations by 35% and enabling ...

Separately, Databricks said it has found a new fine-tuning method that leverages Test-time Adaptive Optimization, a type of ...

As artificial intelligence continues to evolve at an unprecedented pace, a new organization has emerged to address one of the ...

The report outlines how IoT devices, from RFID tags and GPS trackers to smart shelves and robotic pickers, are increasingly ...