Victoria Krakovna

According to our database, Victoria Krakovna authored at least 18 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The Ethics of Advanced AI Assistants.

Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomasev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika

CoRR, 2024

Evaluating Frontier Models for Dangerous Capabilities.

Mary Phuong, Matthew Aitchison, Elliot Catt, Sarah Cogan, Alexandre Kaskasoli, Victoria Krakovna, David Lindner, Matthew Rahtz, Yannis Assael, Sarah Hodkinson, Heidi Howard, Tom Lieberum, Ramana Kumar, Maria Abi Raad, Albert Webson, Lewis Ho, Sharon Lin, Sebastian Farquhar, Marcus Hutter, Grégoire Delétang, Anian Ruoss, Seliem El-Sayed, Sasha Brown, Anca D. Dragan, Rohin Shah, Allan Dafoe, Toby Shevlane

CoRR, 2024

Limitations of Agents Simulated by Predictive Models.

Raymond Douglas, Jacek Karwowski, Chan Bae, Andis Draguns, Victoria Krakovna

CoRR, 2024

Quantifying stability of non-power-seeking in artificial agents.

Evan Ryan Gunter, Yevgeny Liokumovich, Victoria Krakovna

CoRR, 2024

2023

Power-seeking can be probable and predictive for trained agents.

Victoria Krakovna, János Kramár

CoRR, 2023

2022

Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals.

Rohin Shah, Vikrant Varma, Ramana Kumar, Mary Phuong, Victoria Krakovna, Jonathan Uesato, Zac Kenton

CoRR, 2022

2021

Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective.

Tom Everitt, Marcus Hutter, Ramana Kumar, Victoria Krakovna

Synth., 2021

2020

Avoiding Tampering Incentives in Deep RL via Decoupled Approval.

Jonathan Uesato, Ramana Kumar, Victoria Krakovna, Tom Everitt, Richard Ngo, Shane Legg

CoRR, 2020

REALab: An Embedded Perspective on Tampering.

Ramana Kumar, Jonathan Uesato, Richard Ngo, Tom Everitt, Victoria Krakovna, Shane Legg

CoRR, 2020

Avoiding Side Effects By Considering Future Tasks.

Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Penalizing Side Effects using Stepwise Relative Reachability.

Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019

Modeling AGI Safety Frameworks with Causal Influence Diagrams.

Tom Everitt, Ramana Kumar, Victoria Krakovna, Shane Legg

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019

2018

Measuring and avoiding side effects using relative reachability.

Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg

CoRR, 2018

2017

AI Safety Gridworlds.

Jan Leike, Miljan Martic, Victoria Krakovna, Pedro A. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau, Shane Legg

CoRR, 2017

Reinforcement Learning with a Corrupted Reward Channel.

Tom Everitt, Victoria Krakovna, Laurent Orseau, Marcus Hutter, Shane Legg

CoRR, 2017

Reinforcement Learning with a Corrupted Reward Channel.

Tom Everitt, Victoria Krakovna, Laurent Orseau, Shane Legg

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input.

Cory Shain, William Bryce, Lifeng Jin, Victoria Krakovna, Finale Doshi-Velez, Timothy A. Miller, William Schuler, Lane Schwartz

Proceedings of the COLING 2016, 2016

2010

A Generalized-Zero-Preserving Method for Compact Encoding of Concept Lattices.

Matthew Skala, Victoria Krakovna, János Kramár, Gerald Penn

Proceedings of the ACL 2010, 2010