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Turning city traffic into a computer: Novel approach to AI could slash energy demands

What if traffic could compute? This may sound strange, but researchers at Tohoku University's WPI-AIMR have unveiled a bold ...
EurekAlert!

Computing using real life traffic, novel approach to AI cuts its energy usage

What if that traffic associated with the daily commute could be put towards computing? It may sound like a stretch, but that is what researchers from Tohoku University have recently proposed, ...
GitHub

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...
IEEE

Research on LLRF Feedback Control Algorithm Based on Reinforcement Learning

Abstract: This study proposes a low-level radio frequency (LLRF) feedback control algorithm based on reinforcement learning (RL) using the soft actor–critic (SAC) and proximal policy optimization (PPO ...
IEEE

Multi-Agent Optimizing Traffic Light Signals Using Deep Reinforcement Learning

Abstract: In recent years, rapid urbanization has led to increased traffic congestion, rendering traditional traffic light control methods ineffective. Deep Reinforcement Learning (DRL) has emerged as ...