Call for Papers

The deadline for submissions is September 18, 2021 11:59pm PDT.
Update: We are extending the submission deadline to October 4, 2021 11:59pm PDT.

Submissions are now closed. Decisions will be announced by October 22, 2021.


Papers are solicited in research topics at the intersection of machine learning and decision-making, including:

  • Machine learning methods for predicting risky choices / decisions under risk

  • Using machine learning to predict actions in games: normal form, extensive form, repeated

  • New datasets and benchmarks related to choices and decisions

  • Using machine learning for theory development in economics and behavioral decision making

  • Hybrid models combining theoretical knowledge and data driven approaches in predicting decisions

  • Uses of machine learning in Neuroeconomics

  • Machine learning based approaches in modeling and predicting moral actions

  • Machine learning based approaches in modeling and predicting voting

  • Reinforcement learning for modeling and predicting sequential decisions

  • NLP for modeling and predicting decisions

  • RNNs and transformers for building predictive models of humans' decisions

  • Interpretability, transparency and ethical issues arising in using machine learning to predict, understand, or make decisions

  • Leveraging machine learning to improve decision-making in applications (e.g., healthcare, law, banking)

  • Discrete choice and machine learning

  • Theoretical analysis of machine learning methods to predict actions of agents that deviate from the standard utility maximization paradigm: agents with biases, boundedly rational agents


Logistics

All submissions will be private and anonymous. Papers should be 3-4 pages (excluding references), and formatted in NeurIPS style anonymously. Accepted papers will be presented as posters during the workshop, and will optionally be posted on the workshop website if the authors desire. Authors may optionally add appendices in their submitted paper. The final submission including main paper, references and appendix should not exceed 15 pages. Supplementary Materials uploads are to only be used optionally for extra videos/code/data/figures and should be uploaded separately in the submission website.

Submissions will be evaluated based on novelty, rigor, and relevance to theme of the workshop. Both empirical and theoretical contributions are welcome. Submissions should not have previously appeared in a journal or conference (including accepted papers to NeurIPS 2021) and should not be submitted to another NeurIPS workshop. Submissions must adhere to the NeurIPS Code of Conduct.

The 3 highest scoring papers will give recorded oral presentations to maximize the outreach and impact of the authors' work.


Reviewing Committee

Mayank Agrawal (Princeton)

Kristen Altenburger (Facebook)

Amel Awadelkarim (Stanford)

Sudeep Bhatia (UPenn)

Amanda Bower (Twitter)

Gecia Bravo-Hermsdorf (Google)

Kathleen Cachel (WPI)

Mingbo Cai (University of Tokyo)

Fred Callaway (Princeton)

Irene Y. Chen (MIT)

Geri Dimas (WPI)

Kate Donahue (Cornell)

Greg d’Eon (UBC)

Vael Gates (Stanford)

Aviv Netanyahu (MIT)

Kerem Oktar (Princeton)

Jan Overgoor (Stanford)

Marios Papachristou (Cornell)

Ori Plonsky (Technion)

Richard Lanas Phillips (Cornell)

Stephen Ragain (Twitter)

Arjun Seshadri (Amazon)

Nisheeth Srivastava (IIT Kanpur)

Aaron Tucker (Cornell)

Andrew Wang (Cornell)

Gal Yona (Weizmann)

Shuran Zheng (Harvard)