Stephan Tao Zheng

Personal Details

First Name:	Stephan
Middle Name:	Tao
Last Name:	Zheng
Suffix:
RePEc Short-ID:	pzh895
	[This author has chosen not to make the email address public]
	http://www.stephanzheng.com

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Stephan Zheng & Alexander Trott & Sunil Srinivasa & Nikhil Naik & Melvin Gruesbeck & David C. Parkes & Richard Socher, 2020. "The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies," Papers 2004.13332, arXiv.org.

   Cited by:

   1. Artem Kuriksha, 2021. "An Economy of Neural Networks: Learning from Heterogeneous Experiences," Papers 2110.11582, arXiv.org.
   2. Jan Balaguer & Raphael Koster & Ari Weinstein & Lucy Campbell-Gillingham & Christopher Summerfield & Matthew Botvinick & Andrea Tacchetti, 2022. "HCMD-zero: Learning Value Aligned Mechanisms from Data," Papers 2202.10122, arXiv.org, revised May 2022.
   3. Hinterlang, Natascha & Tänzer, Alina, 2021. "Optimal monetary policy using reinforcement learning," Discussion Papers 51/2021, Deutsche Bundesbank.
   4. Sætra, Henrik Skaug, 2020. "A shallow defence of a technocracy of artificial intelligence: Examining the political harms of algorithmic governance in the domain of government," Technology in Society, Elsevier, vol. 62(C).
   5. Nelson Vadori & Leo Ardon & Sumitra Ganesh & Thomas Spooner & Selim Amrouni & Jared Vann & Mengda Xu & Zeyu Zheng & Tucker Balch & Manuela Veloso, 2022. "Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations," Papers 2210.07184, arXiv.org, revised Aug 2023.
   6. Edward Hill & Marco Bardoscia & Arthur Turrell, 2021. "Solving Heterogeneous General Equilibrium Economic Models with Deep Reinforcement Learning," Papers 2103.16977, arXiv.org.
   7. Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
      • Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
   8. May, Ross & Huang, Pei, 2023. "A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets," Applied Energy, Elsevier, vol. 334(C).
   9. Alexander Trott & Sunil Srinivasa & Douwe van der Wal & Sebastien Haneuse & Stephan Zheng, 2021. "Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist," Papers 2108.02904, arXiv.org.
   10. Song-Ju Kim & Taiki Takahashi & Kazuo Sano, 2021. "A balance for fairness: fair distribution utilising physics," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-9, December.
   11. Callum Rhys Tilbury, 2022. "Reinforcement Learning for Economic Policy: A New Frontier?," Papers 2206.08781, arXiv.org, revised Feb 2023.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-EXP: Experimental Economics (1) 2020-05-18. Author is listed
2. NEP-PBE: Public Economics (1) 2020-05-18. Author is listed

Corrections

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