Distributed and Automated Games and Managerial Economics Lab
The research subjects of lab are algorithmic game theory, Internet and blockchain economics, theory of multi-agents and deep reinforcement learning. We focus on the methodological studies for the interactions of human with agents, in the epistemological changes with respect to acquisition of data and information, equilibrium and game dynamics among human and agents, computational and communication complexity, design and analysis of algorithms and protocols. We are especially interested in applications in the Internet market design, analysis of incentives and cooperative competition, as well as high performance consensus, reputation system design, as well as cross-chain mechanism design in Blockchain economics and technology.
Algorithmic Game Theory, Computational Economics, Blockchain, Combinatorics and Optimization
1. Y. Cheng, X. Deng, Y. Li, "Tightening Up the Incentive Ratio for Resource Sharing Over the Rings," In 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), New Orleans, Louisiana USA, May 18-22, 2020, 127-136.
2. X. Deng, T. Lin, and T. Xiao, "Private Data Manipulation in Optimal Sponsored Search Auction," In Proceedings of The Web Conference 2020 (WWW'20), New York, NY, USA, 2676–2682.
3. M. Zhang, J. Li, Z. Chen, H. Chen, X.Deng, "CycLedger: A Scalable and Secure Parallel Protocol for Distributed Ledger via Sharding," In 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), New Orleans, Louisiana USA, May 18-22, 2020, 358-367.