IEEE

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

Abstract: Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
Microsoft

Multimodal reinforcement learning with agentic verifier for AI agents

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...
VentureBeat

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
GitHub

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. Feburary 9, 2026: 🔥 We released a free interactive demo ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
marktechpost

How to Build, Train, and Compare Multiple Reinforcement Learning Agents in a Custom Trading Environment Using Stable-Baselines3

In this tutorial, we explore advanced applications of Stable-Baselines3 in reinforcement learning. We design a fully functional, custom trading environment, integrate multiple algorithms such as PPO ...
acm.org

Shields for Safe Reinforcement Learning

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 ...
TechCrunch

Meta hires key OpenAI researcher to work on AI reasoning models

Meta has hired a highly influential OpenAI researcher, Trapit Bansal, to work on its AI reasoning models under the company’s new AI superintelligence unit, a person familiar with the matter tells ...
eLife

Dynamics of striatal action selection and reinforcement learning

The authors present a biologically plausible framework for action selection and learning in the striatum that is a fundamental advance in our understanding of possible neural implementations of ...