11 citations · 24 across the 18 of their papers we have counts for
20 papers
PopGen: Generating Semantically Diverse Populations for Zero-Shot Coordination
Paul Teiletche, Kanghyun Ryu, Kyungjoon Park +3
In multi-agent reinforcement learning, exposing a cooperator to partners with diverse strategies during training is key to better collaboration at test time. However, existing meth…
Congestion Games with Heterogeneous Valuations: An Optimal Transport Approach
Pan-Yang Su, Negar Mehr, Shankar Sastry
In emerging urban mobility and logistics applications, such as advanced air mobility, electric vehicle charging, and shared service systems, agents with heterogeneous valuations ch…
Active Inverse Learning in Stackelberg Trajectory Games
William Ward, Yue Yu, Jacob Levy +3
Game-theoretic inverse learning is the problem of inferring a player's objectives from their actions. We formulate an inverse learning problem in a Stackelberg game between a leade…
RAPID: Autonomous Multi-Agent Racing using Constrained Potential Dynamic Games
Yixuan Jia, Maulik Bhatt, Negar Mehr
In this work, we consider the problem of autonomous racing with multiple agents where agents must interact closely and influence each other to compete. We model interactions among…
Distributed Potential iLQR: Scalable Game-Theoretic Trajectory Planning for Multi-Agent Interactions
Zach Williams, Jushan Chen, Negar Mehr
In this work, we develop a scalable, local trajectory optimization algorithm that enables robots to interact with other robots. It has been shown that agents' interactions can be s…
Learning to Influence Vehicles' Routing in Mixed-Autonomy Networks by Dynamically Controlling the Headway of Autonomous Cars
Xiaoyu Ma, Negar Mehr
It is known that autonomous cars can increase road capacities by maintaining a smaller headway through vehicle platooning. Recent works have shown that these capacity increases can…
Pricing for Multi-modal Pickup and Delivery Problems with Heterogeneous Users
Mark Beliaev, Negar Mehr, Ramtin Pedarsani
In this paper, we study the pickup and delivery problem with multiple transportation modalities, and address the challenge of efficiently allocating transportation resources while…
Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing
Klara Nahrstedt, Naresh Shanbhag, Vikram Adve +25
In 2021, the Coordinated Science Laboratory CSL, an Interdisciplinary Research Unit at the University of Illinois Urbana-Champaign, hosted the Future of Computing Symposium to cele…
Efficient Constrained Multi-Agent Trajectory Optimization using Dynamic Potential Games
Maulik Bhatt, Yixuan Jia, Negar Mehr
Although dynamic games provide a rich paradigm for modeling agents' interactions, solving these games for real-world applications is often challenging. Many real-world interactive…
Stackelberg Routing of Autonomous Cars in Mixed-Autonomy Traffic Networks
Maxwell Kolarich, Negar Mehr
As autonomous cars are becoming tangible technologies, road networks will soon be shared by human-driven and autonomous cars. However, humans normally act selfishly which may resul…
Concept Representation Learning with Contrastive Self-Supervised Learning
Daniel T. Chang
Concept-oriented deep learning (CODL) is a general approach to meet the future challenges for deep learning: (1) learning with little or no external supervision, (2) coping with te…
Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions
Negar Mehr, Mingyu Wang, Mac Schwager
In this paper, we study the problem of multiple stochastic agents interacting in a dynamic game scenario with continuous state and action spaces. We define a new notion of stochast…
Decentralized Role Assignment in Multi-Agent Teams via Empirical Game-Theoretic Analysis
Fengjun Yang, Negar Mehr, Mac Schwager
We propose a method, based on empirical game theory, for a robot operating as part of a team to choose its role within the team without explicitly communicating with team members,…
Potential iLQR: A Potential-Minimizing Controller for Planning Multi-Agent Interactive Trajectories
Talha Kavuncu, Ayberk Yaraneri, Negar Mehr
Many robotic applications involve interactions between multiple agents where an agent's decisions affect the behavior of other agents. Such behaviors can be captured by the equilib…
Congestion-aware Bi-modal Delivery Systems Utilizing Drones
Mark Beliaev, Negar Mehr, Ramtin Pedarsani
Bi-modal delivery systems are a promising solution to the challenges posed by the increasing demand of e-commerce. Due to the potential benefit drones can have on logistics network…
RAT iLQR: A Risk Auto-Tuning Controller to Optimally Account for Stochastic Model Mismatch
Haruki Nishimura, Negar Mehr, Adrien Gaidon +1
Successful robotic operation in stochastic environments relies on accurate characterization of the underlying probability distributions, yet this is often imperfect due to limited…
An Extended Game-Theoretic Model for Aggregate Lane Choice Behavior of Vehicles at Traffic Diverges with a Bifurcating Lane
Ruolin Li, Negar Mehr, Roberto Horowitz
Road network junctions, such as merges and diverges, often act as bottlenecks that initiate and exacerbate congestion. More complex junction configurations lead to more complex dri…
Pricing Traffic Networks with Mixed Vehicle Autonomy
Negar Mehr, Roberto Horowitz
In a traffic network, vehicles normally select their routes selfishly. Consequently, traffic networks normally operate at an equilibrium characterized by Wardrop conditions. Howeve…
How Will the Presence of Autonomous Vehicles Affect the Equilibrium State of Traffic Networks?
Negar Mehr, Roberto Horowitz
It is known that connected and autonomous vehicles are capable of maintaining shorter headways and distances when they form platoons of vehicles. Thus, such technologies can result…
A Game Theoretic Macroscopic Model of Bypassing at Traffic Diverges with Applications to Mixed Autonomy Networks
Negar Mehr, Ruolin Li, Roberto Horowitz
Vehicle bypassing is known to negatively affect delays at traffic diverges. However, due to the complexities of this phenomenon, accurate and yet simple models of such lane change…