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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Weijie Wang

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#reinforcement learning Open access Oct 2026

Event-Triggered Pinning Control for Cooperative Ramp Merging in Mixed Traffic via Graph Reinforcement Learning

This paper proposes event-triggered pinning graph reinforcement learning (EPGRL) for cooperative ramp merging in mixed traffic with connected and automated vehicles (CAVs) and human-driven vehicles. EPGRL represents vehicle interactions as a time-varying directed graph and uses a dual-stream graph encoder with temporal...

Can Wang, Zhi-Yu Wang, Wei-Jie Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

ProcessLight: Process Supervision for Large Language Model Based Traffic Signal Control

This work proposes an LLM-based framework ProcessLight to decompose signal decisions into verifiable semantic steps and develops Step-wise Traffic Process Policy Optimization (STeP-PO), a novel reinforcement learning framework that optimizes structured reasoning processes through step-level credit assignment.

Huai-Tao Zhao, Tianlong Zhou, Wei-Jie Wang et al. · 0 citations
Open access Aug 2026

Cold-Start Traffic State Forecasting at Unseen Sensor Locations via Support-Conditioned Meta-Graph Learning

Support-conditioned sensor-adaptive meta-graph learning (SC-SAMG) is proposed, which derives target-node representations and spatial dependencies from a short support period and consistently outperforms fine-tuned gated recurrent unit (GRU), adaptive graph convolutional recurrent network (AGCRN), and diffusion convolut...

Can Wang, Zhiyu Wang, Weijie Wang et al. · 0 citations
Open access Aug 2026

STGFormer: Spatio-Temporal Graph Transformer for Traffic Flow Prediction in Sparse-Sensing Scenarios

An improved Transformer prediction model that integrates a graph convolutional network (GCN) and a self-attention mechanism is proposed for traffic flow prediction, combining temporal self-attention and learnable temporal encoding to capture both long-term traffic evolution patterns and sudden fluctuations.

Jin Zhang, Feng-Min Tan, Wei Bai et al. · 0 citations

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