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RL- IIoT-related

Contributors: Wenhao Wu

Network Scheduling

Cellular network traffic scheduling with deep reinforcement learning, Sandeep Chinchali et al 2018, AAAI.

Present a reinforcement learning (RL) based scheduler that can dynamically adapt to traffic variation.

Learning Scheduling Algorithms for Data Processing Clusters, Hongzi Mao et al 2019, SIGCOMM.

Develop new representations for jobs' dependency and conduct real experiments on Spark.

ReLeS: A Neural Adaptive Multipath Scheduler based on Deep Reinforcement Learning, Han Zhang et al 2019, IEEE INFOCOM.

A scheduler with an training algorithm that enables parallel execution of packet scheduling, data collecting, and neural network training.

Deep_Reinforcement_Learning_for_User_Association_and_Resource_Allocation_in_Heterogeneous_Cellular_Networks, Nan Zhao et al 2019, IEEE Transactions on Wireless Communications.

Develop a distributed optimization method based on multi-agent RL.

Adaptive Video Streaming for Massive MIMO Networks via Approximate MDP and Reinforcement Learning, Qiao Lan et al 2020, IEEE Transactions on Wireless Communications.

Consider a MDP with random user arrivals and departures.

Workshop Scheduling

Relative value function approximation for the capacitated re-entrant line scheduling problem, Jin Young Choi et al 2005, IEEE Transactions on Automation Science and Engineering.

A Reinforcement Learning Approach to Robust Scheduling of Semiconductor Manufacturing Facilities, In-Beom Park et al 2020, IEEE Transactions on Automation Science and Engineering.

Deep reinforcement learning in production systems: a systematic literature review, Xiaocong Chen et al 2021, International Journal of Production Research.

Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning, Libing Wang et al 2021, Computer Networks.

Other Scheduling Problem

A deep q-network for the beer game: A reinforcement learning algorithm to solve inventory optimization problems, Afshin Oroojlooyjadid et al 2017.

Use RL in a simply case of the supply chain.

Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning, Kaixiang Lin et al 2018, KDD.

A special case of bin packing problem solved by RL.

ORL Reinforcement Learning Benchmarks for Online Stochastic Optimization, Bharathan Balaji et al 2018, Amazon Report.

Applying RL algorithms to a range of practical applications.