Graph-based collaborative multi-agent deep reinforcement learning for reconfigurable job shop scheduling

#reinforcement learning Open access Nov 2026

Service-effort trade-offs in large-scale bike-sharing rebalancing: A hierarchical reinforcement learning framework with imitation-based warm-starting

Igor Betkier, Philipp Otto, Damian Wierzbicki et al. · Applied Soft Computing · 0 citations

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#reinforcement learning Open access Nov 2026

Uncertainty-aware reinforcement learning for joint optimization of data center operations and electricity market bidding

Zhanhua Pan, Qiong Liu, Xiao Liu et al. · Applied Energy · 0 citations

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#reinforcement learning Oct 2026

Dynamic obstacle avoidance for autonomous vehicles in complex traffic environments: A guidance-enhanced deep reinforcement learning approach

Zhiyao Pan, Chen Chen, Yahui Liu et al. · Engineering applications of... · 0 citations

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#reinforcement learning Nov 2026

Deep reinforcement learning for adaptive rack repositioning and pod sequencing in robotic mobile fulfillment systems via multi-fidelity simulation optimization

Chun-Chih Chiu, Wei-Ming Kuo · Advanced Engineering Informa... · 0 citations

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#reinforcement learning Nov 2026

A multi-agent deep reinforcement learning framework for coordinated urban traffic signal and parking lot exit control

Yuchuan Du, Wenjie Shen, Chenglong Liu et al. · Transportation Research Part... · 0 citations

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#reinforcement learning Open access Oct 2026

LLM powered adaptive traffic signal control via knowledge-enhanced prompt and reinforcement learning fine-tuning

Mingqian Tang, Chunhui Yu, Can Li et al. · Transportation Research Part... · 0 citations

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MIT News · Artificial Intelligence · news.mit.edu Aug 18, 2026

When AI art has no author: Study finds generated images often can’t be traced to training data

A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

Hugging Face Blog · huggingface.co Aug 13, 2026

What We Learned by Reproducing 2,200 papers from ICML

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

MIT News · Artificial Intelligence · news.mit.edu Aug 3, 2026

Alexander Rakhlin named director of the MIT Statistics and Data Science Center

An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.

Google Research Blog · research.google Jul 22, 2026

Towards a quantum computer that learns from its errors

Machine Intelligence