Program Overview

	Oct. 24
9:00	Workshop 1
9:30	Workshop on Imitation Learning: Single-Agent & Multi-Agent	Tutorial 1 Reinforcement Learning via Convex Duality by Ofir Nachum (Google)
12:30~14:00	Lunch
14:00~17:00	Workshop 2 Workshop on Autonomous Driving Competition	Tutorial 2 OneFlow: A Novel Deep Learning Framework Born for Large Scale Distributed Training by Jinhui Yuan (OneFlow)

	Oct. 25
9:00	Workshop 3
9:30	The 5th Asian Workshop on Reinforcement Learning	Tutorial 3 Deep Multi-Agent Reinforcement Learning: Direct and Game-Theoretical Approaches by Ying Wen (SJTU)
12:30~14:00	Lunch
14:00~17:00	Workshop 4 Workshop on Evaluation in Multi-Agent Reinforcement Learning

	Oct. 26
9:15~9:30	Opening
9:30~10:30	Keynote 1 by John E. Hopcroft An Introduction to AI and Deep Learning
10:30~10:40	Coffee Break
10:40~12:00	Session 1: Reinforcement Learning
12:00~13:30	Lunch
13:30~14:30	Keynote 2 by Qiang Yang Federated Learning and Distributed AI
14:30~14:40	Coffee Break
14:40~16:00	Session 2: Multiagent Reinforcement Learning
16:00~16:50	Session 3: Computational Game
16:50~18:00	Session 4: Multiagent Applications

	Oct. 27
9:30~10:30	Keynote 3 by Le Song A Framework for Differentiable Discovery of Distributed Local Algorithms on Graphs
10:30~10:40	Coffee Break
10:40~12:00	Session 5: Multiagent Coordination & Communication
12:00~13:30	Lunch
13:30~14:30	Session 6: Industry Talks From Huawei Noah's Ark Lab, Netease Games, and Inspir.ai
14:30~14:40	Coffee Break
14:40~15:40	Keynote 4 by Jun Wang Multiagent Variational Bayes
15:40~19:00	Poster Session