109 citations · 689 across the 65 of their papers we have counts for
72 papers
Chance-Constrained Trajectory Planning with Multimodal Environmental Uncertainty
Kai Ren, Heejin Ahn, Maryam Kamgarpour
We tackle safe trajectory planning under Gaussian mixture model (GMM) uncertainty. Specifically, we use a GMM to model the multimodal behaviors of obstacles' uncertain states. Then…
A Policy Iteration Algorithm for N-player General-Sum Linear Quadratic Dynamic Games
Yuxiang Guan, Giulio Salizzoni, Maryam Kamgarpour +1
We present a policy iteration algorithm for the infinite-horizon N-player general-sum deterministic linear quadratic dynamic games and compare it to policy gradient methods. We dem…
Multi-Agent Learning in Contextual Games under Unknown Constraints
Anna M. Maddux, Maryam Kamgarpour
We consider the problem of learning to play a repeated contextual game with unknown reward and unknown constraints functions. Such games arise in applications where each agent's ac…
Identifiability and Generalizability in Constrained Inverse Reinforcement Learning
Andreas Schlaginhaufen, Maryam Kamgarpour
Two main challenges in Reinforcement Learning (RL) are designing appropriate reward functions and ensuring the safety of the learned policy. To address these challenges, we present…
On Linear Quadratic Potential Games
Sara Hosseinirad, Giulio Salizzoni, Alireza Alian Porzani +1
Our paper addresses characterizing conditions for a linear quadratic (LQ) game to be a potential game. The desired properties of potential games in finite action settings, such as…
Safe Zeroth-Order Optimization Using Linear Programs
Baiwei Guo, Yang Wang, Yuning Jiang +2
To solve unmodeled optimization problems with hard constraints, this paper proposes a novel zeroth-order approach called Safe Zeroth-order Optimization using Linear Programs (SZO-L…
Convergence Rate of Learning a Strongly Variationally Stable Equilibrium
Tatiana Tatarenko, Maryam Kamgarpour
We derive the rate of convergence to the strongly variationally stable Nash equilibrium in a convex game, for a zeroth-order learning algorithm. Though we do not assume strong mono…
Safe Zeroth-Order Optimization Using Quadratic Local Approximations
Baiwei Guo, Yuning Jiang, Giancarlo Ferrari-Trecate +1
This paper addresses black-box smooth optimization problems, where the objective and constraint functions are not explicitly known but can be queried. The main goal of this work is…
Certification of Bottleneck Task Assignment with Shortest Path Criteria
Tony A. Wood, Maryam Kamgarpour
Minimising the longest travel distance for a group of mobile robots with interchangeable goals requires knowledge of the shortest length paths between all robots and goal destinati…
Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations
Baiwei Guo, Yuning Jiang, Maryam Kamgarpour +1
We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge i…
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning
Ilnura Usmanova, Yarden As, Maryam Kamgarpour +1
Optimizing noisy functions online, when evaluating the objective requires experiments on a deployed system, is a crucial task arising in manufacturing, robotics and many others. Of…
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation
Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
We consider model-based multi-agent reinforcement learning, where the environment transition model is unknown and can only be learned via expensive interactions with the environmen…
On the Rate of Convergence of Payoff-based Algorithms to Nash Equilibrium in Strongly Monotone Games
Tatiana Tatarenko, Maryam Kamgarpour
We derive the rate of convergence to Nash equilibria for the payoff-based algorithm proposed in \cite{tat_kam_TAC}. These rates are achieved under the standard assumption of convex…
Distributionally Robust Bootstrap Optimization
Tyler Summers, Maryam Kamgarpour
Control architectures and autonomy stacks for complex engineering systems are often divided into layers to decompose a complex problem and solution into distinct, manageable sub-pr…
Fast Projection Onto Convex Smooth Constraints
Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause +1
The Euclidean projection onto a convex set is an important problem that arises in numerous constrained optimization tasks. Unfortunately, in many cases, computing projections is co…
Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety Guarantees
Vasileios Lefkopoulos, Maryam Kamgarpour
We tackle the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain time-varying locations. The uncertainties are modeled using widely acc…
Safe Motion Planning against Multimodal Distributions based on a Scenario Approach
Heejin Ahn, Colin Chen, Ian M. Mitchell +1
We present the design of a motion planning algorithm that ensures safety for an autonomous vehicle. In particular, we consider a multimodal distribution over uncertainties; for exa…
Contextual Games: Multi-Agent Learning with Side Information
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause +1
We formulate the novel class of contextual games, a type of repeated games driven by contextual information at each round. By means of kernel-based regularity assumptions, we model…
Actuator Placement for Structural Controllability beyond Strong Connectivity and towards Robustness
Baiwei Guo, Orcun Karaca, Sepide Azhdari +2
Actuator placement is a fundamental problem in control design for large-scale networks. In this paper, we study the problem of finding a set of actuator positions by minimizing a g…
Multi-robot task allocation for safe planning against stochastic hazard dynamics
Daniel Tihanyi, Yimeng Lu, Orcun Karaca +1
We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and…
Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid
Orcun Karaca, Daniel Tihanyi, Maryam Kamgarpour
This letter studies the problem of minimizing increasing set functions, or equivalently, maximizing decreasing set functions, over the base of a matroid. This setting has received…
A market-based approach for enabling inter-area reserve exchange
Orcun Karaca, Stefanos Delikaraoglou, Maryam Kamgarpour
Considering the sequential clearing of energy and reserves in Europe, enabling inter-area reserve exchange requires optimally allocating inter-area transmission capacities between…
Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems
Yang Zheng, Luca Furieri, Maryam Kamgarpour +1
This paper studies a class of partially observed Linear Quadratic Gaussian (LQG) problems with unknown dynamics. We establish an end-to-end sample complexity bound on learning a ro…
Bandit Learning in Convex Non-Strictly Monotone Games
Tatiana Tatarenko, Maryam Kamgarpour
We address learning Nash equilibria in convex games under the payoff information setting. We consider the case in which the game pseudo-gradient is monotone but not necessarily str…