Micah Carroll

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Recommender Systems

Reactive Agents

Reinforcement Learning

Sequential Decision Problems

Top Venues

Publications

Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan
AI Alignment with Changing and Influenceable Reward Functions. CoRR (2024)
Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine
Defining Deception in Decision Making. AAMAS (2024)
Micah Carroll, Alan Chan, Henry Ashton, David Krueger
Characterizing Manipulation from AI Systems. EAAMO (2023)
Smitha Milli, Micah Carroll, Sashrika Pandey, Yike Wang, Anca D. Dragan
Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization. CoRR (2023)
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023)
Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
Harms from Increasingly Agentic Algorithmic Systems. FAccT (2023)
Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D. Dennis, Stuart Russell
Who Needs to Know? Minimal Knowledge for Optimal Coordination. ICML (2023)
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR (2023)
Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
Harms from Increasingly Agentic Algorithmic Systems. CoRR (2023)
Micah Carroll, Alan Chan, Henry Ashton, David Krueger
Characterizing Manipulation from AI Systems. CoRR (2023)
Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael Dennis, Stuart Russell
Who Needs to Know? Minimal Knowledge for Optimal Coordination. CoRR (2023)
Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca D. Dragan, Sam Devlin
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR (2022)
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca D. Dragan, Sam Devlin
UniMASK: Unified Inference in Sequential Decision Problems. CoRR (2022)
Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. CoRR (2022)
Mesut Yang, Micah Carroll, Anca D. Dragan
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration. CoRR (2022)
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS (2022)
David Zhang, Micah Carroll, Andreea Bobu, Anca D. Dragan
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking. CoRR (2022)
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
Evaluating the Robustness of Collaborative Agents. AAMAS (2021)
Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan
Estimating and Penalizing Preference Shift in Recommender Systems. RecSys (2021)
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
Evaluating the Robustness of Collaborative Agents. CoRR (2021)
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
On the Utility of Learning about Humans for Human-AI Coordination. CoRR (2019)
Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
On the Utility of Learning about Humans for Human-AI Coordination. NeurIPS (2019)