IJTCS | 大会特邀报告介绍（一）

编者按

首届国际理论计算机联合大会（International Joint Conference on Theoretical Computer Science，IJTCS）将于2020年8月17日-21日在线上举行，由北京大学与中国工业与应用数学学会（CSIAM）、中国计算机学会（CCF）、国际计算机学会中国委员会（ACM China Council）联合主办，北京大学前沿计算研究中心承办。  

大会简介 → 国际理论计算机联合大会重磅登场

大会特邀报告人

Silvio Micali

美国麻省理工大学教授，图灵奖得主，密码学、信息安全等领域的知名学者，区块链协议Algorand负责人

蔡进一

美国威斯康星麦迪逊大学教授，理论计算科学领域的知名学者，曾获得美国总统青年学者奖和Alfred P. Sloan Research Fellow 等荣誉

应明生

悉尼科技大学杰出教授，主要研究领域包括形式化方法、量子计算与量子信息、计算机科学与人工智能中的逻辑学、模糊逻辑等

汪  军

英国伦敦大学学院教授、阿兰·图灵研究所Turing Fellow，研究领域为多智能体强化学习、博弈论、机制设计等

孙晓明

中国科学院计算技术研究所研究员，主要研究领域为算法与计算复杂性、量子计算、社交网络算法等

陆品燕

上海财经大学教授，主要研究领域包括近似计数、计数问题的复杂性、算法博弈论、全息算法等

本期带来三个大会特邀报告简介，以飨读者。

Model-Checking Quantum Markov Chains

Abstract

Model-checking is one of the dominant techniques for verification of computer (hardware and software) systems. It automatically checks whether a desired property is satisfied by a system. The properties that are checked are usually specified in a logic, in particular, temporal logic; typical properties are deadlock freedom, invariants, safety, request-response properties. The systems under checking are mathematically modelled as e.g. (finite-state) automata, transition systems, Markov chains and Markov decision processes.

In this talk, I'll discuss the essential difficulties in developing model-checking techniques for quantum systems that are never present in model checking classical systems, and review a new line of researches pursued by the author and their collaborators on checking general quantum systems modelled as quantum Markov chains, including quantum computing and communication hardware and software.

Biography

Mingsheng Ying graduated from Department of Mathematics, Fuzhou Teachers College, Jiangxi, China, in 1981. He is a Distinguished Professor with and the Research Director of the Center for Quantum Computation and Intelligent Systems (QCIS), Faculty of Engineering and Information Technology, University of Technology Sydney, Australia, and Cheung Kong Professor with the State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China.

Mingsheng Ying's research interests are quantum computation, programming theory, and foundations of artificial intelligence. He has published more than 100 papers in top international journals and conferences. He is the author of the books "Foundations of Quantum Programming" (Elsevier - Morgan Kaufmann 2016) and "Topology in Process Calculus: Approximate Correctness and Infinite Evolution of Concurrent Programs" (Springer-Verlag, 2001).

Multi-Agent Learning

Abstract

Multi-agent learning arises in a variety of domains where intelligent agents interact not only with the (unknown) environment but also with each other. It has an increasing number of applications ranging from controlling a group of autonomous vehicles/robots/drones to coordinating collaborative bots in production lines, optimizing distributed sensor networks/traffic, and machine bidding in competitive e-commerce and financial markets, just to name a few.

Yet, the non-stationary nature calls for new theory that brings interactions into the learning process. In this talk, I shall provide an up-to-date introduction on the theory and methods of multi-agent AI, with a focus on competition, collaboration, and communications among intelligent agents. The studies in both game theory and machine learning will be examined in a unified treatment. I shall also sample our recent work on the subject including mean-field multiagent reinforcement learning, stochastic potential games, and solution concepts beyond Nash-equilibrium.

Biography

Jun Wang is Chair Professor, Computer Science, University College London, and Founding Director of MSc Web Science and Big Data Analytics. He is also Co-founder and Chief Scientist in MediaGamma Ltd, a UCL start-up company focusing on AI for intelligent audience decision making.

Prof. Jun Wang's main research interests are in the areas of AI and intelligent systems, including (multiagent) reinforcement learning, deep generative models, and their diverse applications on information retrieval, recommender systems and personalization, data mining, smart cities, bot planning, computational advertising etc. His team won the first global real-time bidding algorithm contest with 80+ participants worldwide. Jun has published over 100 research papers and is a winner of multiple "Best Paper" awards. He was a recipient of the Beyond Search – Semantic Computing and Internet Economics award by Microsoft Research and also received Yahoo! FREP Faculty award. He has served as an Area Chair in ACM CIKM and ACM SIGIR. His recent service includes co-chair of Artificial Intelligence, Semantics, and Dialog in ACM SIGIR 2018. MediaGamma has received the UCLB One-to-Watch award 2016.

He has more than 15 years track records of advising the industry and knowledge transfer. He was a technical advisor for startups such as Last.Fm, Passiv Systems, Massive Analytic, Context Scout, and Polecat, and had various projects with BT, Microsoft, Yahoo!, Alibaba, Didi etc.

Prof. Wang obtained his PhD degree in Delft University of Technology, the Netherlands; MSc degree in National University of Singapore, Singapore; and Bachelor degree in Southeast University, Nanjing, China.

Optimal Mechanism Design: Simplicity and Robustness

Abstract

Mechanism design is a central topic of microeconomics. We focus on revenue maximizing auctions in this talk. We will first introduce the celebrated Myerson's optimal auction and discuss the assumptions made by Myerson. We motivate the mechanism design problem of relaxing the assumptions and discuss some of the exciting work regarding the simplicity and robustness of auctions.

This talk is based on the following joint works:

• Yaonan Jin, Pinyan Lu, Qi Qi, Zhihao Gavin Tang, Tao Xiao: Tight approximation ratio of anonymous pricing. STOC 2019

• Yaonan Jin, Pinyan Lu, Zhihao Gavin Tang, Tao Xiao: Tight Revenue Gaps among Simple Mechanisms. SODA 2019

• Xiaohui Bei, Nick Gravin, Pinyan Lu, Zhihao Gavin Tang: Correlation-Robust Analysis of Single Item Auction. SODA 2019

• Nick Gravin, Pinyan Lu: Separation in Correlation-Robust Monopolist Problem with Budget. SODA 2018

Biography

Dr. Pinyan Lu is a professor and the founding director of Institute for Theoretical Computer Science at Shanghai University of Finance and Economics (ITCS@SUFE). Before joining SUFE, he was a researcher at Microsoft Research. He is also a Chair Professor at Computer Science Department and Zhiyuan College of Shanghai Jiao Tong University. He studied in Tsinghua University (BS (2005) and PhD (2009) both in Computer Science). He is interested in theoretical computer science, including complexity theory, algorithms design and algorithmic game theory. Currently, his research is mainly focused on complexity and approximability of counting problems, and algorithmic mechanism design.

大会主席

John Hopcroft

中国科学院外籍院士、北京大学访问讲席教授

林惠民

中国科学院院士、中国科学院软件研究所专家

大会联合主席

邓小铁

北京大学教授

顾问委员会主席

高  文

中国工程院院士、北京大学教授

梅  宏

中国科学院院士、CCF理事长

张平文

中国科学院院士、CSIAM理事长、北京大学教授

组织单位

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大会网站：

https://econcs.pku.edu.cn/ijtcs2020/IJTCS2020.html

注册链接：

https://econcs.pku.edu.cn/ijtcs2020/Registration.htm

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