Security Boulevard

NDSS 2025 – TrajDeleter: Enabling Trajectory Forgetting In Offline Reinforcement Learning Agents

Machine Unlearning Authors, Creators & Presenters: hen Gong (University of Vriginia), Kecen Li (Chinese Academy of Sciences), ...

Reinforcement learning and organizational management

Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
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 ...
Frontiers

A combined approach to lithology identification using reinforcement learning and transformer algorithms

Lithology identification plays a pivotal role in logging interpretation during drilling operations, directly influencing drilling decisions and efficiency. Conventional lithology identification ...
IEEE

Online Reinforcement Learning Algorithm Design for Adaptive Optimal Consensus Control Under Interval Excitation

Abstract: This article proposes online data-based reinforcement learning (RL) algorithm for adaptive output consensus control of heterogeneous multiagent systems (MASs) with unknown dynamics. First, ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
Frontiers

Intelligent maneuver decision-making for UAVs using the TD3–LSTM reinforcement learning algorithm under uncertain information

Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
IEEE

A TD3-Based Reinforcement Learning Algorithm With Curriculum Learning for Adaptive Yaw Control in All-Wheel-Drive Electric Vehicles

Abstract: A novel artificial intelligence-based approach for the direct yaw control (DYC) of an all-wheel drive (AWD) electric vehicle (EV) is proposed in this paper. To improve adaptability and ...
VentureBeat

MiniMax-M1 is a new open source model with 1 MILLION TOKEN context and new, hyper efficient reinforcement learning

Chinese AI startup MiniMax, perhaps best known in the West for its hit realistic AI video model Hailuo, has released its latest large language model, MiniMax-M1 — and in great news for enterprises and ...