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Publication search results
found 270 matches
- 2024
- W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI 2024: 10066-10073 - Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine:
Defining Deception in Decision Making. AAMAS 2024: 2111-2113 - Andreea Bobu
, Andi Peng
, Pulkit Agrawal
, Julie A. Shah
, Anca D. Dragan
:
Aligning Human and Robot Representations. HRI 2024: 42-54 - Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons:
When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. CoRR abs/2402.17747 (2024) - Cassidy Laidlaw, Shivam Singhal, Anca D. Dragan:
Preventing Reward Hacking with Occupancy Measure Regularization. CoRR abs/2403.03185 (2024) - Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
A Generalized Acquisition Function for Preference-based Reward Learning. CoRR abs/2403.06003 (2024) - 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:
Evaluating Frontier Models for Dangerous Capabilities. CoRR abs/2403.13793 (2024) - Jerry Zhi-Yang He, Sashrika Pandey, Mariah L. Schrum, Anca D. Dragan:
CoS: Enhancing Personalization and Mitigating Bias with Context Steering. CoRR abs/2405.01768 (2024) - Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. CoRR abs/2405.17713 (2024) - Michelle Pan, Mariah Schrum, Vivek Myers, Erdem Biyik, Anca D. Dragan:
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. CoRR abs/2406.06714 (2024) - Erik Jones, Anca D. Dragan, Jacob Steinhardt:
Adversaries Can Misuse Combinations of Safe Models. CoRR abs/2406.14595 (2024) - Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR abs/2406.17098 (2024) - 2023
- Ivan Cvitic
, Dragan Perakovic
, Marko Perisa
, Anca D. Jurcut
:
Methodology for Detecting Cyber Intrusions in e-Learning Systems during COVID-19 Pandemic. Mob. Networks Appl. 28(1): 231-242 (2023) - Ivan Cvitic
, Dragan Perakovic
, Marko Perisa
, Anca D. Jurcut
:
Correction to: Methodology for Detecting Cyber Intrusions in e-Learning Systems during COVID-19 Pandemic. Mob. Networks Appl. 28(1): 243 (2023) - Daniel Shin, Anca D. Dragan, Daniel S. Brown:
Benchmarks and Algorithms for Offline Preference-Based Reward Learning. Trans. Mach. Learn. Res. 2023 (2023) - Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown, Anca D. Dragan:
The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types. AAAI 2023: 5983-5992 - Jerry Zhi-Yang He, Daniel S. Brown, Zackory Erickson, Anca D. Dragan:
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. CoRL 2023: 1865-1886 - Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine:
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL 2023: 3894-3908 - Andreea Bobu
, Yi Liu
, Rohin Shah
, Daniel S. Brown
, Anca D. Dragan
:
SIRL: Similarity-based Implicit Representation Learning. HRI 2023: 565-574 - Ran Tian
, Masayoshi Tomizuka
, Anca D. Dragan
, Andrea Bajcsy
:
Towards Modeling and Influencing the Dynamics of Human Learning. HRI 2023: 350-358 - Joey Hong, Kush Bhatia, Anca D. Dragan:
On the Sensitivity of Reward Inference to Misspecified Human Models. ICLR 2023 - Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown:
Causal Confusion and Reward Misidentification in Preference-Based Reward Learning. ICLR 2023 - Gaurav Rohit Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan:
Contextual Reliability: When Different Features Matter in Different Contexts. ICML 2023: 11300-11320 - Erik Jones, Anca D. Dragan, Aditi Raghunathan, Jacob Steinhardt:
Automatically Auditing Large Language Models via Discrete Optimization. ICML 2023: 15307-15329 - Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. IROS 2023: 7523-7530 - Joey Hong, Sergey Levine, Anca D. Dragan:
Learning to Influence Human Behavior with Offline Reinforcement Learning. NeurIPS 2023 - Cassidy Laidlaw, Stuart J. Russell, Anca D. Dragan:
Bridging RL Theory and Practice with the Effective Horizon. NeurIPS 2023 - Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan:
SIRL: Similarity-based Implicit Representation Learning. CoRR abs/2301.00810 (2023) - Ran Tian, Masayoshi Tomizuka, Anca D. Dragan, Andrea Bajcsy:
Towards Modeling and Influencing the Dynamics of Human Learning. CoRR abs/2301.00901 (2023) - Daniel Shin, Anca D. Dragan, Daniel S. Brown:
Benchmarks and Algorithms for Offline Preference-Based Reward Learning. CoRR abs/2301.01392 (2023)
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