Academic Papers
  • Succinct and Robust Multi-Agent Communication With Temporal Message Control NIPS 2020

  • Multi-agent active perception with prediction rewards NIPS 2020

  • Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning NIPS 2020

  • Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity NIPS 2020

  • Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning NIPS 2020

  • Learning Multi-Agent Communication through Structured Attentive Reasoning NIPS 2020

  • Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning NIPS 2020

  • Robust Multi-Agent Reinforcement Learning with Model Uncertainty NIPS 2020

  • Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning NIPS 2020

  • Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward NIPS 2020

  • Contextual Games: Multi-Agent Learning with Side Information NIPS 2020

  • Learning Individually Inferred Communication for Multi-Agent Cooperation NIPS 2020

  • EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning NIPS 2020

  • Joint Policy Search for Multi-agent Collaboration with Imperfect Information NIPS 2020

  • "ATTENTION, LEARN TO SOLVE ROUTING PROBLEMS!" in conference paper at ICLR 2019

  • "DeepViNE: Virtual Network Embedding with Deep Reinforcement Learning," IEEE INFOCOM 2019.
  • 03월 05일 (월) 논문 세미나 – 임현교
    H. Yao, X. Chen, P. Zhang and L. Wang, "A novel reinforcement learning algorithm for virtual network embedding," Neurocomputing, 2018.

  • 03월 22일 (월) 논문 세미나 – 김주봉
    Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson, "Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning," NIPS, 2020.

  • 03월 15일 (월) 논문 세미나 – 최호빈
    Christianos, Filippos, Lukas Schäfer, and Stefano V. Albrecht, "Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning," arXiv preprint arXiv:2006.07169, 2020.

  • 03월 08일 (월) 논문 세미나 – 지창훈
    Scott Fujimoto, et al., "Addressing Function Approximation Error in Actor-Critic Methods", International Conference on Machine Learning, 2018.

  • 03월 02일 (화) 논문 세미나 – 임현교
    Z. Yan, et al., "Automatic Virtual Network Embedding: A Deep Reinforcement Learning Approach With Graph Convolutional Networks," IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol. 38, No. 6, June, 2020.

  • 02월 08일 (월) 논문 세미나 – 울라 이산
    Khoa Nguyen, et al., "Efficient Virtual Network Embedding with Node Ranking and Intelligent Link Mapping," IEEE 9th International Conference on Cloud Networking (CloudNet), November, 2020.

  • 02월 01일 (월) 논문 세미나 – 김주봉
    Yong Liu, et al., "Multi-Agent Game Abstraction via Graph Attention Neural Network," AAAI, 2020.

  • 01월 25일 (월) 논문 세미나 – 최호빈
    Enright, John J., and Peter R. Wurman, "Optimization and coordinated autonomy in mobile fulfillment systems," Workshops at the twenty-fifth AAAI conference on artificial intelligence, 2011.

  • 01월 27일 (수) 논문 세미나 – 울라 이산
    Min Feng, et al., "Virtual Network Embedding based on Modified Genetic Algorithm," Peer-to-Peer Networking and Applications, October 2019.

  • 01월 18일 (월) 논문 세미나 – 지창훈
    Mohammed Hossny, et al., "Refined Continuous Control of DDPG Actors via Parametrised Activation," arXiv:2006.02818, June 2020.

  • 01월 11일 (월) 논문 세미나 – 임현교
    Mosharaf Chowdhury, et al., "ViNEYard: Virtual Network Embedding Algorithms With Coordinated Node and Link Mapping," IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 20, NO. 1, FEBRUARY 2012.

  • 01월 04일 (월) 논문 세미나 – 황규영
    Tuomas Haarnoja, et al., "Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor," ICML 2018.
  • 12월 21일 (화) 논문 세미나 – 최호빈, 김주봉
    Anuj Mahajan, et al., "MAVEN: Multi-Agent Variational Exploration," NeurIPS, 7611-7622, 2019.

  • 12월 14일 (월) 논문 세미나 – 울라 이산
    M. Feng, et al., "Topology-Aware Virtual Network Embedding Through the Degree," National Doctoral Academic Forum on Information and Communications Technology 2013, Aug, 2013.

  • 11월 16일 (월) 논문 세미나 – 임현교
    Fengsheng Wei et al., “Network Slice Reconfiguration by Exploiting Deep Reinforcement Learning with Large Action Space,” IEEE Transactions on Network and Service Management, 2020.

  • 11월 09일 (월) 논문 세미나 – 김주봉
    Kyunghwan Son et al., “QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement learning,” Proceedings of the 36th International Conference on Machine Learning, 2019.

  • 11월 02일 (월) 논문 세미나 – 울라 이산
    Haozhe Wanga et al., “Data-driven dynamic resource scheduling for network slicing: A Deep reinforcement learning approach,” Information Sciences, 498, pp. 106-116, 2019.

  • 10월 19일 (월) 논문 세미나 – 지창훈
    S. Vassilaras et al., “Applying Deep Learning and Reinforcement Learning to Traveling Salesman Problem” in IEEE International Conference on Systems, Man, and Cybernetics(SMC). Aug .2018.

  • 10월 05일 (월) 논문 세미나 – 임현교
    S. Vassilaras et al., “The Algorithmic Aspects of Network Slicing,” in IEEE Communications Magazine, vol. 55, no. 8, pp. 112-119, Aug. 2017.

  • 09월 28일 (월) 논문 세미나 – 김주봉
    Yuki Miyashita and Toshiharu Sugawara, “Analysis of coordinated behavior structures with multi-agent deep reinforcement learning,”, Applied Intelligence, 2020.

  • 09월 21일 (월) 논문 세미나 – 지창훈
    Galina L. Rogova, Jyotsna Kasturi, "Reinforcement Learning Neural Network For Distributed Decision Making",2002

  • 09월 14일 (월) 논문 세미나 – 임현교
    J. Du, X. Huang, F. Wu and S. Leng, "Reinforcement Learning Empowered QoS-aware Adaptive Q-Routing in Ad-hoc Networks," 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, pp. 551-556, 2020.

  • 09월 07일 (월) 논문 세미나 – 최호빈
    Yali Du, Lei Han, Meng Fang, Tianhong Dai, Ji Liu, Dacheng Tao, "LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning," NIPS, 2019.

  • 07월 30일 (목) 논문 세미나 – 임현교
    Q. Fu, E. Sun, K. Meng, M. Li and Y. Zhang, "Deep Q-Learning for Routing Schemes in SDN-Based Data Center Networks," in IEEE Access, vol. 8, pp. 103491-103499, 2020.

  • 07월 23일 (목) 논문 세미나 – 황규영
    Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy, “Deep Exploration via Bootstrapped DQN,” Advances in Neural Information Processing Systems 29 (NIPS 2016).

  • 02월 17일 (월) 논문 세미나 – 최호빈
    Zäzilia Seibold, Thomas Stoll, Kai Furmans, “Layout-optimized sorting of goods with decentralized controlled conveying modules,” 2013 IEEE International Systems Conference (SysCon), Apr. 2013.

  • 02월 11일 (화) 논문 세미나 – 김주봉
    T. Eccles et al., “Biases for Emergent Communication in Multi-agent Reinforcement Learning,”, NIPS, 2019.

  • 02월 03일 (월) 교재 세미나 – 황규영
    Richard S. Sutton and Andrew G. Barto, “Reinforcement Learning: An Introduction,” second edition, MIT Press, Cambridge, MA, 2018.

  • 01월 20일 (월) 논문 세미나 – 임현교


  • 01월 17일 (금) 논문 세미나 – 황규영
    Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar, David Silver, “Rainbow: Combining Improvements in Deep Reinforcement Learning,” AAAI, 2018.

  • 01월 06일 (월) 논문 세미나 – 최호빈


  • 05월 27일 (월) 논문 세미나 – 임현교

  • 05월 13, 20일 (월) 논문 세미나 – 권도형

  • 05월 08일 (수) 논문 세미나 – 황규영
    François Chollet, “Xception: Deep Learning with Depthwise Separable Convolutions”, arXiv:1610.02357v3 [cs.CV] 4 Apr 2017.

  • 04월 29일 (월) 논문 세미나 – 최호빈

  • 04월 08일 (월) 논문 세미나 – 임현교

  • 04월 01일 (월) 논문 세미나 – 허주성

  • 03월 25일 (월) 논문 세미나 – 최호빈


  • 03월 18일 (월) 논문 세미나 – 황규영
    Sartoretti, Y. Wu, W. Paivine, T. K. S. Kumar, S. Koenig, and H. Choset, “Distributed Reinforcement Learning for MultiRobot Decentralized Collective Construction”, DARS 2018.

  • 03월 11일 (월) 논문 세미나 – 임현교

  • 03월 4일 (월) 논문 세미나 – 김주봉

  • 02월 25일 (월) 논문 세미나 – 김주봉

  • 02월 15일 (금) 논문 세미나 – 권도형

  • 02월 07일 (목) 논문 세미나 – 임현교

  • 01월 31일 (목) 논문 세미나 – 김주봉


    • 12월 20일 (목) 논문 세미나 – 임현교
      M. Spryn, A. Sharma, D. Parkar, and M. Shrimal, "Distributed Deep Reinforcement Learning on the Cloud for Autonomous Driving," ACM/IEEE 1st International Workshop on Software Engineering for AI in Autonomous Systems, 2018.

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