A note on the proportionality between some consistency indices in the AHP. - Matteo Brunelli; Andrew Critch; Michele Fedrizzi (Appl. Math. Comput., 2013)

Parametric Bounded Löb's Theorem and Robust Cooperation of Bounded Agents. - Andrew Critch (CoRR, 2016)

Logical Induction. - Scott Garrabrant; Tsvi Benson-Tilsen; Andrew Critch; Nate Soares; Jessica Taylor (Electron. Colloquium Comput. Complex., 2016)

Toward negotiable reinforcement learning: shifting priorities in Pareto optimal sequential decision-making. - Andrew Critch (CoRR, 2017)

A Formal Approach to the Problem of Logical Non-Omniscience. - Scott Garrabrant; Tsvi Benson-Tilsen; Andrew Critch; Nate Soares; Jessica Taylor (TARK, 2017)

Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making. - Andrew Critch; Stuart Russell 001 (CoRR, 2017)

Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making. - Nishant Desai; Andrew Critch; Stuart J. Russell (NeurIPS, 2018)

A parametric, Resource-Bounded Generalization of löB's Theorem, and a robust Cooperation criterion for Open-Source Game Theory. - Andrew Critch (J. Symb. Log., 2019)

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. - Michael Dennis 001; Natasha Jaques; Eugene Vinitsky; Alexandre M. Bayen; Stuart Russell 001; Andrew Critch; Sergey Levine (NeurIPS, 2020)

The MAGICAL Benchmark for Robust Imitation. - Sam Toyer; Rohin Shah; Andrew Critch; Stuart Russell 001 (NeurIPS, 2020)

Neural Networks are Surprisingly Modular. - Daniel Filan; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2020)

AI Research Considerations for Human Existential Safety (ARCHES). - Andrew Critch; David Krueger 001 (CoRR, 2020)

Multi-Principal Assistance Games: Definition and Collegial Mechanisms. - Arnaud Fickinger; Simon Zhuang; Andrew Critch; Dylan Hadfield-Menell; Stuart Russell 001 (CoRR, 2020)

Accumulating Risk Capital Through Investing in Cooperation. - Charlotte Roman; Michael Dennis 001; Andrew Critch; Stuart Russell 001 (AAMAS, 2021)

Aligning AI With Shared Human Values. - Dan Hendrycks; Collin Burns; Steven Basart; Andrew Critch; Jerry Li 001; Dawn Song; Jacob Steinhardt (ICLR, 2021)

Optimal Policies Tend To Seek Power. - Alexander Matt Turner; Logan Smith; Rohin Shah; Andrew Critch; Prasad Tadepalli (NeurIPS, 2021)

Clusterability in Neural Networks. - Daniel Filan; Stephen Casper; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

Detecting Modularity in Deep Neural Networks. - Shlomi Hod; Stephen Casper; Daniel Filan; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

Human irrationality: both bad and good for reward inference. - Lawrence Chan; Andrew Critch; Anca D. Dragan (CoRR, 2021)

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. - Scott Emmons; Caspar Oesterheld; Andrew Critch; Vincent Conitzer; Stuart Russell 001 (ICML, 2022)

WordSig: QR streams enabling platform-independent self-identification that's impossible to deepfake. - Andrew Critch (CoRR, 2022)

Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory. - Andrew Critch; Michael Dennis 001; Stuart Russell 001 (CoRR, 2022)

Machine learning corroborates subjective ratings of walking and balance difficulty in multiple sclerosis. - Wenting Hu; Owen Combden; Xianta Jiang; Syamala Buragadda; Caitlin J. Newell; Maria C. Williams; Andrew Critch; Michelle Ploughman (Frontiers Artif. Intell., 2022)

TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI. - Andrew Critch; Stuart Russell 001 (CoRR, 2023)

Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online. - Steven Adler; Zoë Hitzig; Shrey Jain; Catherine Brewer; Wayne Chang; Renee DiResta; Eddy Lazzarin; Sean McGregor; Wendy Seltzer; Divya Siddarth; Nouran Soliman; Tobin South; et al. (CoRR, 2024)

A Taxonomy of Omnicidal Futures Involving Artificial Intelligence. - Andrew Critch; Jacob Tsimerman (CoRR, 2025)