Workshop 1: DAI 2022 Workshop on Learning and Optimization

Organizers:

Abstract:

In recent years, the optimization and computational intelligence methods have achieved remarkable results in domains including games, robotics, circuit design, and autonomous driving. This workshop will bring together researchers working in the field of optimization, reinforcement learning, and evolutionary computation, and it will also cover cutting-edge research both in academic and industrial communities. It aims to help interested researchers both inside and outside of the field gain a high-level view about the current state-of-the-art works and potential directions and applications for future.

Schedule (Dec 15, 2022, 9:00 - 10:20 & 10:30 - 12:30 UTC+8, RoomB):

Time Talker Talk Title Affiliation
09:00-09:40 李勇 AI-empowered Energy Consumption Optimization and Carbon Emissions Reduction
in Launching 5G Mobile Networks		 清华大学
09:00-09:40 张启超 Opportunities and Challenges of Reinforcement Learning in Autonomous Driving 中国科学院
自动化研究所
10:20-10:30 Coffee Break
10:30-11:10 钱超 Multi-objective Evolutionary Learning: Advances in Theories and Algorithms 南京大学
11:10-11:50 杨宁 Reinforcement Learning for Operation Research 中国科学院
自动化研究所


Workshop 2: Big Decision Models

Organizers:

Abstract:

Large sequence models, which feature a great volume of parameters and auto-regressive data processing, have recently provided significant assistance for prediction tasks and (self-)supervised learning in natural language processing (NLP) and computer vision (CV). In the last two years, sequence models, especially the Transformer, have attracted rapidly increasing interest in the RL communities and spawned many approaches. Besides, large sequence models are emerging in decision-making and reinforcement learning (RL) with noticeable effectiveness and generalizability, which implies the potential of building a Big Decision Model (BDM)for general purposes, that is, a large sequence model leveraging a large number of parameters for hundreds or more decision-making tasks like what large sequence models did for NLP and CV. Our workshop is a half-day workshop on BDMs at DAI 2022, with the aim to provide a venue, which can bring together academic researchers and industry practitioners (i) to discuss the potentials, principles, and applications of BDMs and (ii) to foster research on innovative algorithms, novel techniques, and new frameworks for BDMs.

Schedule (Dec 15, 2022, 14:00 - 15:10 & 15:30 - 17:10 UTC+8, RoomB):

14:00-14:10 Openning
Speaker: Ying Wen

Affiliation: Shanghai Jiao Tong University

14:10-14:40 Large Scale Reinforcement Learning in Industrial Problems: Challenges and Opportunities
Speaker: Jiangcheng Zhu

Affiliation: Huawei Cloud

14:40-15:10 A General Feedback System Encoder and its Applications
Speaker: Fanming Luo

Affiliation: Polixir

15:10-15:30 Coffee Break

15:30-16:00 Offline Pre-trained Multi-Agent Reinforcement Learning
Speaker: Linghui Meng

Affiliation: Institute of Automation, Chinese Academy of Sciences

16:00-16:30 Pretraining in Deep Reinforcement Learning: A Survey
Speaker: Zhihui Xie

Affiliation: Shanghai Jiao Tong University & Tencent

16:30-17:00 DB1: A Practice of Intelligent Decision-Making Foundation Model
Speaker: Ziyu Wan

Affiliation: Shanghai Jiao Tong University & Digital Brain Lab

17:00-17:10 Closing
Speaker: Weinan Zhang

Affiliation: Shanghai Jiao Tong University