A Handful of Perspective Papers in EconCS, sorted by topic.

Multi-Agent Systems

• Parsons, S., and Wooldridge, M. (2002). Game theory and decision theory in multi-agent systems. In AAMAS. [Link]
• Shoham, Y., Powers, R., & Grenager, T. (2007). If multi-agent learning is the answer, what is the question?. Artificial intelligence. [Link]

Computational Social Choice

• Anshelevich, E., Filos-Ratsikas, A., Shah, N., and Voudouris, A. A. (2021). Distortion in social choice problems: The first 15 years and beyond. IJCAI. [Link]
• Faliszewski, P., and Procaccia, A. D. (2010). AI’s war on manipulation: Are we winning?. AI Magazine. [Link]

Economics and Computation

• Sandholm, T. (2008). Computing in mechanism design. New Palgrave Dictionary of Economics. [Link]
• Parkes, D. C., and Wellman, M. P. (2015). Economic reasoning and artificial intelligence. Science. [Link]
• Einav, L., and Levin, J. (2014). Economics in the age of big data. Science. [Link]

Multi-Agent Reinforcement Learning

• Nowé, A., Vrancx, P., & De Hauwere, Y. M. (2012). Game theory and multi-agent reinforcement learning. Reinforcement Learning: State-of-the-Art. [Link]

Networks, Crowds, and Markets

• Kempe, D., Kleinberg, J., and Tardos, É. (2003). Maximizing the spread of influence through a social network. In Proceedings of SIGKDD. [Link]
• Easley, D., and Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge university press. [Link]
• Axelrod, R. (1997). The Dissemination of Culture: A Model with Local Convergence and Global Polarization. The Journal of Conflict Resolution. [Link]

Consumer Choice

• Gilboa, I., Postlewaite, A., and Schmeidler, D. (2021). The complexity of the consumer problem. Research in Economics. [Link]
• Hainmueller, J., Hopkins, D. J., & Yamamoto, T. (2014). Causal inference in conjoint analysis: Understanding multidimensional choices via stated preference experiments. Political analysis. [Link]

Computational Social Science

• Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A. L., Brewer, D., … and Van Alstyne, M. (2009). Computational social science. Science. [Link]
• Adamic, L. A., & Glance, N. (2005). The political blogosphere and the 2004 US election: divided they blog. In Proceedings of the 3rd international workshop on Link discovery. [Link]
• Pentland, A. (2014) Social Physics: How Good Ideas Spread-The Lessons from a New Science. [Amazon]

Cognitive Science

• Camerer, C. F., Ho, T. H., and Chong, J. K. (2004). A cognitive hierarchy model of games. The Quarterly Journal of Economics. [Link] (See also Keynes’s ‘Beauty Contest’.)
• Camerer, C. F. (2011). Behavioral game theory: Experiments in strategic interaction. Princeton university press. [Link]

Ethics and AI

• Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., … and Rahwan, I. (2018). The moral machine experiment. Nature. [Link]

Prediction, Learning, and Games

• Young, H. P. (1996). The economics of convention. Journal of economic perspectives. [Link]
• Fudenberg, D., & Levine, D. K. (1998). The theory of learning in games. MIT press. [Link]
• Young, H. P. (2004). Strategic learning and its limits. OUP Oxford. [Link]
• Cesa-Bianchi, N., & Lugosi, G. (2006). Prediction, learning, and games. Cambridge university press. [Link]
• Hart, S., and Mas-Colell, A. (2013). Simple adaptive strategies: from regret-matching to uncoupled dynamics. World Scientific. [Link]

AI Economics

• Horton, J. J. (2023). Large language models as simulated economic agents: What can we learn from homo silicus?. National Bureau of Economic Research. [Link]
• Zheng, S., Trott, A., Srinivasa, S., Naik, N., Gruesbeck, M., Parkes, D. C., and Socher, R. (2020). The AI economist: Improving equality and productivity with ai-driven tax policies. [Link]