Analyzing Human Models that Adapt Online. - Andrea Bajcsy; Anand Siththaranjan; Claire J. Tomlin; Anca D. Dragan (ICRA, 2021)

On the Computational Consequences of Cost Function Design in Nonlinear Optimal Control. - Tyler Westenbroek; Anand Siththaranjan; Mohsin Sarwari; Claire J. Tomlin; S. Shankar Sastry (CDC, 2022)

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. - 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; et al. (Trans. Mach. Learn. Res., 2023)

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. - Anand Siththaranjan; Cassidy Laidlaw; Dylan Hadfield-Menell (ICLR, 2024)

AI Alignment with Changing and Influenceable Reward Functions. - Micah Carroll; Davis Foote; Anand Siththaranjan; Stuart Russell 001; Anca D. Dragan (ICML, 2024)

Intent Demonstration in General-Sum Dynamic Games via Iterative Linear-Quadratic Approximations. - Jingqi Li 001; Anand Siththaranjan; Somayeh Sojoudi; Claire J. Tomlin; Andrea Bajcsy (CoRR, 2024)