99 citations · 100 across the 18 of their papers we have counts for
22 papers
Dynamic Auction Mechanisms in a Closed-Credit Economy: Sequential Slot Reallocation in Air Traffic Management
Jihun Kim, Pan-Yang Su, Maria G. Mendoza +3
Indivisible resources allocated in advance may need to be reallocated when capacity reductions make existing assignments infeasible, yet monetary compensation is often impractical…
Persistent LLM Orchestration of Heterogeneous Robot Teams via Partial Delegation to Multi-Agent Protocols
Maria G. Mendoza, Victoria M. Tuck, Zachary Ravichandran +2
Natural language specifications let non-expert users task robot teams, and large language models (LLMs) have recently proven effective at grounding such semantic specifications int…
Orchestrating Level- Policies Against Unknown Opponents in Partially-Observable Dynamic Games
Addison Kalanther, Sanika Bharvirkar, Daniel Bostwick +2
Level- reasoning generates a hierarchy of policies specialized to opponents with different reasoning levels. When an opponent's level is unknown, a common deployment rule estima…
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…
Hierarchical Generative Agents for Simulating Sequential Human Behavior
Maria G. Mendoza, Lucas Waldburger, Jin Lee +1
Complex cognitive, emotional, and social processes shape human evacuations during natural disasters. Accurate modeling and understanding of human behavior in disasters or emergenci…
Dynamic Multi-Robot Task Allocation under Uncertainty and Communication Constraints: A Game-Theoretic Approach
Maria G. Mendoza, Pan-Yang Su, Bryce L. Ferguson +1
We study dynamic multi-robot task allocation under uncertain task completion, time-window constraints, and incomplete information. Tasks arrive online over a finite horizon and mus…
NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning
Addison Kalanther, Sanika Bharvirkar, Shankar Sastry +1
Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, training MARL algorithms in general-…
Game-to-Real Gap: Quantifying the Effect of Model Misspecification in Network Games
Bryce L. Ferguson, Chinmay Maheshwari, Manxi Wu +1
Game-theoretic models and solution concepts provide rigorous tools for predicting collective behavior in multi-agent systems. In practice, however, different agents may rely on dif…
Average Unfairness in Routing Games
Pan-Yang Su, Arwa Alanqary, Bryce L. Ferguson +3
We propose average unfairness as a new measure of fairness in routing games, defined as the ratio between the average latency and the minimum latency experienced by users. This mea…
Evader-Agnostic Team-Based Pursuit Strategies in Partially-Observable Environments
Addison Kalanther, Daniel Bostwick, Chinmay Maheshwari +1
We consider a scenario where a team of two unmanned aerial vehicles (UAVs) pursue an evader UAV within an urban environment. Each agent has a limited view of their environment wher…
Coordinated Autonomous Drones for Human-Centered Fire Evacuation in Partially Observable Urban Environments
Maria G. Mendoza, Addison Kalanther, Daniel Bostwick +3
Autonomous drone technology holds significant promise for enhancing search and rescue operations during evacuations by guiding humans toward safety and supporting broader emergency…
Two-Stage Mechanism Design for Electric Vehicle Charging with Day-Ahead Reservations
Pan-Yang Su, Yi Ju, Scott Moura +1
We propose a general two-period model where electrical vehicles (EVs) can reserve charging sessions in the day-ahead market and swap them in the real-time market. Under the model,…
α-RACER: Real-Time Algorithm for Game-Theoretic Motion Planning and Control in Autonomous Racing using Near-Potential Function
Dvij Kalaria, Chinmay Maheshwari, Shankar Sastry
Autonomous racing extends beyond the challenge of controlling a racecar at its physical limits. Professional racers employ strategic maneuvers to outwit other competing opponents t…
Privacy Preserving Mechanisms for Coordinating Airspace Usage in Advanced Air Mobility
Chinmay Maheshwari, Maria G. Mendoza, Victoria Marie Tuck +5
Advanced Air Mobility (AAM) operations are expected to transform air transportation while challenging current air traffic management practices. By introducing a novel market-based…
Convergence of Decentralized Actor-Critic Algorithm in General-sum Markov Games
Chinmay Maheshwari, Manxi Wu, Shankar Sastry
Markov games provide a powerful framework for modeling strategic multi-agent interactions in dynamic environments. Traditionally, convergence properties of decentralized learning a…
Adaptive Incentive Design with Learning Agents
Chinmay Maheshwari, Kshitij Kulkarni, Manxi Wu +1
We propose an adaptive incentive mechanism that learns the optimal incentives in environments where players continuously update their strategies. Our mechanism updates incentives b…
Understanding the Impact of Coalitions between EV Charging Stations
Sukanya Kudva, Kshitij Kulkarni, Chinmay Maheshwari +2
The rapid growth of electric vehicles (EVs) is driving the expansion of charging infrastructure globally. As charging stations become ubiquitous, their substantial electricity cons…
Incentive-Compatible Vertiport Reservation in Advanced Air Mobility: An Auction-Based Approach
Pan-Yang Su, Chinmay Maheshwari, Victoria Tuck +1
The rise of advanced air mobility (AAM) is expected to become a multibillion-dollar industry in the near future. Market-based mechanisms are touted to be an integral part of AAM op…
Congestion Pricing for Efficiency and Equity: Theory and Applications to the San Francisco Bay Area
Chinmay Maheshwari, Kshitij Kulkarni, Druv Pai +3
Congestion pricing, while adopted by many cities to alleviate traffic congestion, raises concerns about widening socioeconomic disparities due to its disproportionate impact on low…
Hacking Predictors Means Hacking Cars: Using Sensitivity Analysis to Identify Trajectory Prediction Vulnerabilities for Autonomous Driving Security
Marsalis Gibson, David Babazadeh, Claire Tomlin +1
Adversarial attacks on learning-based multi-modal trajectory predictors have already been demonstrated. However, there are still open questions about the effects of perturbations o…
Follower Agnostic Methods for Stackelberg Games
Chinmay Maheshwari, James Cheng, S. Shankar Sasty +2
In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner. Unlike previous works, our approach…
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
Joshua Achiam, Shankar Sastry
Exploration in complex domains is a key challenge in reinforcement learning, especially for tasks with very sparse rewards. Recent successes in deep reinforcement learning have bee…