Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games

Mapping Intimacies ◽

10.1109/smc52423.2021.9658625 ◽

2021 ◽

Author(s):

Won Joon Yun ◽

Sungwon Yi ◽

Joongheon Kim

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Strategy Games ◽

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Scalable Multi-agent Reinforcement Learning Architecture for Semi-MDP Real-Time Strategy Games

Neural Computing for Advanced Applications - Communications in Computer and Information Science ◽

10.1007/978-981-15-7670-6_36 ◽

2020 ◽

pp. 433-446

Author(s):

Zhentao Wang ◽

Weiwei Wu ◽

Ziyao Huang

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Strategy Games ◽

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Gym-µRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning

10.1109/cog52621.2021.9619076 ◽

2021 ◽

Author(s):

Shengyi Huang ◽

Santiago Ontanon ◽

Chris Bamford ◽

Lukasz Grela

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

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Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising

Proceedings of the 27th ACM International Conference on Information and Knowledge Management - CIKM '18 ◽

10.1145/3269206.3272021 ◽

2018 ◽

Author(s):

Junqi Jin ◽

Chengru Song ◽

Han Li ◽

Kun Gai ◽

Jun Wang ◽

...

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Display Advertising ◽

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A cooperative multi-agent deep reinforcement learning framework for real-time residential load scheduling

Proceedings of the International Conference on Internet of Things Design and Implementation - IoTDI '19 ◽

10.1145/3302505.3310069 ◽

2019 ◽

Author(s):

Chi Zhang ◽

Sanmukh R. Kuppannagari ◽

Chuanxiu Xiong ◽

Rajgopal Kannan ◽

Viktor K. Prasanna

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Load Scheduling ◽

Learning Framework ◽

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Applying Multi-agent Reinforcement Learning to Autonomous Distributed Real-time Scheduling

Transactions of the Institute of Systems Control and Information Engineers ◽

10.5687/iscie.26.129 ◽

2013 ◽

Vol 26 (4) ◽

pp. 129-137 ◽

Author(s):

Koji Iwamura ◽

Norihisa Mayumi ◽

Yoshitaka Tanimizu ◽

Nobuhiro Sugimura

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Real Time Scheduling ◽

Time Scheduling ◽

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Hierarchical control of multi-agent reinforcement learning team in real-time strategy (RTS) games

Expert Systems with Applications ◽

10.1016/j.eswa.2021.115707 ◽

2021 ◽

pp. 115707

Author(s):

Weigui Jair Zhou ◽

Budhitama Subagdja ◽

Ah-Hwee Tan ◽

Darren Wee-Sze Ong

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Hierarchical Control ◽

Multi Agent ◽

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Real-time bus holding control on a transit corridor based on multi-agent reinforcement learning

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) ◽

10.1109/itsc.2016.7795538 ◽

2016 ◽

Author(s):

Weiya Chen ◽

Kunlin Zhou ◽

Chunxiao Chen

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

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Neuroevolution based multi-agent system for micromanagement in real-time strategy games

Proceedings of the Fifth Balkan Conference in Informatics on - BCI '12 ◽

10.1145/2371316.2371324 ◽

2012 ◽

Author(s):

Iuhasz Gabriel ◽

Viorel Negru ◽

Daniela Zaharie

Keyword(s):

Real Time ◽

Multi Agent System ◽

Agent System ◽

Strategy Games ◽

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Real-Time Order Scheduling in Credit Factories: A Multi-agent Reinforcement Learning Approach

Communications in Computer and Information Science - Intelligent Computing and Block Chain ◽

10.1007/978-981-16-1160-5_36 ◽

2021 ◽

pp. 461-475

Author(s):

Chaoqi Huang ◽

Runbang Cui ◽

Jiang Deng ◽

Ning Jia

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Learning Approach ◽

Order Scheduling ◽

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Real Time Strategy Games: A Reinforcement Learning Approach

Procedia Computer Science ◽

10.1016/j.procs.2015.06.030 ◽

2015 ◽

Vol 54 ◽

pp. 257-264 ◽

Author(s):

Harshit Sethy ◽

Amit Patel ◽

Vineet Padmanabhan

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Learning Approach ◽

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