Paper Presentations

Session 1: Reinforcement Learning (Oct. 26, 10:40)

Efficient Exploration by Novelty-Pursuit (DAI 2020)

Presentation by Ziniu Li (The Chinese University of HongKong, Shenzhen)

MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning (DAI 2020)

Presentation by Haotian Fu (Tianjin University)

D3PG: Decomposed Deep Deterministic Policy Gradient for Continuous Control (DAI 2020)

Presentation by Yinzhao Dong (Dalian University of Technology)

RD^2: Reward Decomposition with Representation Decomposition (NeurIPS 2020)

Presentation by Zichuan Lin (Microsoft Research)

Battery Management for Automated Warehouses via Deep Reinforcement Learning (DAI 2020)

Presentation by Yanchen Deng (Nanyang Technological University)

Session 2: Multiagent Reinforcement Learning (Oct. 26, 14:40)

Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control (DAI 2020)

Presentation by Qingrui Zhang (Delft University of Technology)

Q-value Path Decomposition for Deep Multiagent Reinforcement Learning (ICML 2020)

Presentation by Yaodong Yang (Tianjin University)

ROMA: Multi-Agent Reinforcement Learning with Emergent Roles (ICML 2020)

Presentation by Tonghan Wang (Tsinghua University)

Learning Nearly Decomposable Value Functions via Communication Minimization (ICLR 2020)

Presentation by Jianhao Wang (Tsinghua University)

Multi-Agent Interactions Modeling with Correlated Policies (ICLR 2020)

Presentation by Minghuan Liu (Shanghai Jiao Tong University)

Session 3: Computational Game (Oct. 26, 16:00)

Parallel Algorithm for Nash Equilibrium in Multiplayer Stochastic Games with Application to Naval Strategic Planning (DAI 2020)

Presentation by Sam Ganzfried (Ganzfried Research)

Hybrid Independent Learning in Cooperative Markov Games (DAI 2020)

Presentation by Roi Yehoshua (Northeastern University)

Converging to Team-maxmin Equilibria in Zero-sum Multiplayer Games (ICML 2020)

Presentation by Youzhi Zhang (Nanyang Technological University)

Session 4: Multiagent Applications (Oct. 26, 16:50)

LAC-Nav: Collision-Free Multiagent Navigation Based on The Local Action Cells (DAI 2020)

Presentation by Li Ning (Shenzhen Institutes of Advanced Technology)

Collaborative Data Acquisitions (AAMAS 2020)

Presentation by Wen Zhang (ShanghaiTech University)

Feudal Multi-Agent Deep Reinforcement Learning for Traffic Signal Control (AAMAS 2020)

Presentation by Jinming Ma (University of Science and Technology of China)

Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge (IJCAI 2020)

Presentation by Pinzhuo Tian (Nanjing University)

Session 5: Multiagent Coordination & Communication (Oct. 27, 10:40)

Context-aware Multi-Agent Coordination with Loose Couplings and Repeated Interaction (DAI 2020)

Presentation by Feifei Lin (Nanyang Technological University)

Bi-level Actor-Critic for Multi-agent Coordination (AAAI 2020)

Presentation by Weizhe Chen (Shanghai Jiao Tong University)

Enhancing Centralized Value Functions for Cooperative Multi-agent Reinforcement Learning (AAAI 2020)

Presentation by Xinghu Yao (Nanjing University of Aeronautics and Astronautics)

Learning Efficient Multi-agent Communication: An Information Bottleneck Approach (ICML 2020)

Presentation by Rundong Wang (Nanyang Technological University)

Learning Individually Inferred Communication for Multi-Agent Cooperation (NeurIPS 2020)

Presentation by Ziluo Ding (Peking University)