7 citations · 21 across the 20 of their papers we have counts for
23 papers
Can Play That Game: Online Fitted -Iteration for Continuous-Action Zero-Sum Markov Games with Convex-Concave Function Approximation
Kushagra Gupta, Jingqi Li, Cade Armstrong +4
Zero-sum Markov games arise in a wide variety of sequential decision-making problems such as adversarial learning and planning against modeled uncertainties. However, prior work on…
Residual Denoising Enables Sample-Efficient Multi-Agent Coordination on Demand
Dayi Dong, Maulik Bhatt, Aayushi Shrivastava +2
Pretrained robot policies offer strong manipulation skills but are typically limited to single-agent settings, where a robot acts in isolation. In this work, we study how to adapt…
Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations
Lasse Peters, Laura Ferranti, Andrea Bajcsy +1
Imitation learning powered by generative models has proven effective for modeling complex single-agent behaviors. However, teaching multi-agent systems, like multiple arms or vehic…
Controllability in preference-conditioned multi-objective reinforcement learning
Pau de las Heras Molins, Beyazit Yalcinkaya, Lasse Peters +2
Multi-objective reinforcement learning (MORL) allows a user to express preference over outcomes in terms of the relative importance of the objectives, but standard metrics cannot c…
Homotopy-Guided Potential Games for Congestion-Aware Navigation
Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Lasse Peters, Michael Khayyat +3
We address the multi-agent motion planning problem where interactions, collisions, and congestion co-exist. Conventional game-theoretic planners capture interactions among agents b…
Breaking Exponential Complexity in Games of Ordered Preference: A Tractable Reformulation
Dong Ho Lee, Jingqi Li, Lasse Peters +2
Games of ordered preference (GOOPs) model multi-player equilibrium problems in which each player maintains a distinct hierarchy of strictly prioritized objectives. Existing approac…
Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing
Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2
Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…
Bayesian Inverse Games with High-Dimensional Multi-Modal Observations
Yash Jain, Xinjie Liu, Lasse Peters +2
Many multi-agent interaction scenarios can be naturally modeled as noncooperative games, where each agent's decisions depend on others' future actions. However, deploying game-theo…
Approximate solutions to games of ordered preference
Pau de las Heras Molins, Eric Roy-Almonacid, Dong Ho Lee +3
Autonomous vehicles must balance ranked objectives, such as minimizing travel time, ensuring safety, and coordinating with traffic. Games of ordered preference effectively model th…
Generalizing Safety Beyond Collision-Avoidance via Latent-Space Reachability Analysis
Kensuke Nakamura, Lasse Peters, Andrea Bajcsy
Hamilton-Jacobi (HJ) reachability is a rigorous mathematical framework that enables robots to simultaneously detect unsafe states and generate actions that prevent future failures.…
You Can't Always Get What You Want: Games of Ordered Preference
Dong Ho Lee, Lasse Peters, David Fridovich-Keil
We study noncooperative games, in which each player's objective is composed of a sequence of ordered- and potentially conflicting-preferences. Problems of this type naturally model…
Updating Robot Safety Representations Online from Natural Language Feedback
Leonardo Santos, Zirui Li, Lasse Peters +2
Robots must operate safely when deployed in novel and human-centered environments, like homes. Current safe control approaches typically assume that the safety constraints are know…
Auto-Encoding Bayesian Inverse Games
Xinjie Liu, Lasse Peters, Javier Alonso-Mora +2
When multiple agents interact in a common environment, each agent's actions impact others' future decisions, and noncooperative dynamic games naturally capture this coupling. In in…
Contingency Games for Multi-Agent Interaction
Lasse Peters, Andrea Bajcsy, Chih-Yuan Chiu +4
Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under un…
Scenario-Game ADMM: A Parallelized Scenario-Based Solver for Stochastic Noncooperative Games
Jingqi Li, Chih-Yuan Chiu, Lasse Peters +6
Decision-making in multi-player games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochast…
Online and Offline Learning of Player Objectives from Partial Observations in Dynamic Games
Lasse Peters, Vicenç Rubies-Royo, Claire J. Tomlin +4
Robots deployed to the real world must be able to interact with other agents in their environment. Dynamic game theory provides a powerful mathematical framework for modeling scena…
Cost Inference for Feedback Dynamic Games from Noisy Partial State Observations and Incomplete Trajectories
Jingqi Li, Chih-Yuan Chiu, Lasse Peters +3
In multi-agent dynamic games, the Nash equilibrium state trajectory of each agent is determined by its cost function and the information pattern of the game. However, the cost and…
Learning to Play Trajectory Games Against Opponents with Unknown Objectives
Xinjie Liu, Lasse Peters, Javier Alonso-Mora
Many autonomous agents, such as intelligent vehicles, are inherently required to interact with one another. Game theory provides a natural mathematical tool for robot motion planni…
Learning Mixed Strategies in Trajectory Games
Lasse Peters, David Fridovich-Keil, Laura Ferranti +3
In multi-agent settings, game theory is a natural framework for describing the strategic interactions of agents whose objectives depend upon one another's behavior. Trajectory game…
Inferring Objectives in Continuous Dynamic Games from Noise-Corrupted Partial State Observations
Lasse Peters, David Fridovich-Keil, Vicenç Rubies-Royo +2
Robots and autonomous systems must interact with one another and their environment to provide high-quality services to their users. Dynamic game theory provides an expressive theor…
iLQGames.jl: Rapidly Designing and Solving Differential Games in Julia
Lasse Peters, Zachary N. Sunberg
In many problems that involve multiple decision making agents, optimal choices for each agent depend on the choices of others. Differential game theory provides a principled formal…
Inference-Based Strategy Alignment for General-Sum Differential Games
Lasse Peters, David Fridovich-Keil, Claire J. Tomlin +1
In many settings where multiple agents interact, the optimal choices for each agent depend heavily on the choices of the others. These coupled interactions are well-described by a…
Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Games
David Fridovich-Keil, Ellis Ratner, Lasse Peters +2
Many problems in robotics involve multiple decision making agents. To operate efficiently in such settings, a robot must reason about the impact of its decisions on the behavior of…