3 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety
Justin Wang, Haimin Hu, Duy Phuong Nguyen +1
While robust optimal control theory provides a rigorous framework to compute robot control policies that are provably safe, it struggles to scale to high-dimensional problems, lead…
Think Deep and Fast: Learning Neural Nonlinear Opinion Dynamics from Inverse Dynamic Games for Split-Second Interactions
Haimin Hu, Jaime Fernández Fisac, Naomi Ehrich Leonard +3
Non-cooperative interactions commonly occur in multi-agent scenarios such as car racing, where an ego vehicle can choose to overtake the rival, or stay behind it until a safe overt…
Blending Data-Driven Priors in Dynamic Games
Justin Lidard, Haimin Hu, Asher Hancock +9
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic…
Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots
Haimin Hu, Gabriele Dragotto, Zixu Zhang +3
We consider the multi-agent spatial navigation problem of computing the socially optimal order of play, i.e., the sequence in which the agents commit to their decisions, and its as…
Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity
Kaiqu Liang, Zixu Zhang, Jaime Fernández Fisac
Large language models (LLMs) exhibit advanced reasoning skills, enabling robots to comprehend natural language instructions and strategically plan high-level actions through proper…