106 citations · 290 across the 63 of their papers we have counts for
24 papers · 1 filter
Distributionally Robust Imitation Learning: Layered Control Architecture for Certifiable Autonomy
Aditya Gahlawat, Ahmed Aboudonia, Sandeep Banik +5
Imitation learning (IL) enables autonomous behavior by learning from expert demonstrations. While more sample-efficient than comparative alternatives like reinforcement learning, I…
Invariant Price of Anarchy: a Metric for Welfarist Traffic Control
Ilia Shilov, Mingjia He, Heinrich H. Nax +3
The Price of Anarchy (PoA) is a standard metric for quantifying inefficiency in socio-technical systems, widely used to guide policies like traffic tolling. Conventional PoA analys…
GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding
Johannes Gaber, Meshal Alharbi, Daniele Gammelli +1
Large robot fleets are now common in warehouses and other logistics settings, where small control gains translate into large operational impacts. In this article, we address task s…
FICO: Finite-Horizon Closed-Loop Factorization for Unified Multi-Agent Path Finding
Jiarui Li, Alessandro Zanardi, Federico Pecora +2
Multi-Agent Path Finding is a fundamental problem in robotics and AI, yet most existing formulations treat planning and execution separately and address variants of the problem in…
Hierarchical Strategic Decision-Making in Layered Mobility Systems
Mingjia He, Zhiyu He, Jan Ghadamian +3
Mobility systems are complex socio-technical environments influenced by multiple stakeholders with hierarchically interdependent decisions, rendering effective control and policy d…
Zeroth-Order Constrained Optimization from a Control Perspective via Feedback Linearization
Runyu Zhang, Gioele Zardini, Asuman Ozdaglar +2
Safe derivative-free optimization under unknown constraints is a fundamental challenge in modern learning and control. Existing zeroth-order (ZO) methods typically still assume acc…
Optimism as Risk-Seeking in Multi-Agent Reinforcement Learning
Runyu Zhang, Na Li, Asuman Ozdaglar +2
Risk sensitivity has become a central theme in reinforcement learning (RL), where convex risk measures and robust formulations provide principled ways to model preferences beyond e…
Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Mingjia He, Andrea Censi, Runyu Zhang +2
Network-based systems are inherently interconnected, with the design and performance of subnetworks being interdependent. However, the decisions of self-interested operators may le…
Robust Vehicle Rebalancing with Deep Uncertainty in Autonomous Mobility-on-Demand Systems
Xinling Li, Xiaotong Guo, Qingyi Wang +2
Autonomous Mobility-on-Demand (AMoD) services offer an opportunity for improving passenger service while reducing pollution and energy consumption through effective vehicle coordin…
Reproducibility in the Control of Autonomous Mobility-on-Demand Systems
Xinling Li, Meshal Alharbi, Daniele Gammelli +7
Autonomous Mobility-on-Demand (AMoD) systems, powered by advances in robotics, control, and Machine Learning (ML), offer a promising paradigm for future urban transportation. AMoD…
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks
Vincent Abbott, Kotaro Kamiya, Gerard Glowacki +3
How do we enable artificial intelligence models to improve themselves? This is central to exponentially improving generalized artificial intelligence models, which can improve thei…
Multi-Agent Path Finding via Finite-Horizon Hierarchical Factorization
Jiarui Li, Alessandro Zanardi, Gioele Zardini
We present a novel algorithm for large-scale Multi-Agent Path Finding (MAPF) that enables fast, scalable planning in dynamic environments such as automated warehouses. Our approach…
Wise Goose Chase: A Predictive Path Planning Algorithm for Dynamic Rebalancing in Ride-Hailing Systems
Avalpreet Singh Brar, Rong Su, Christos G. Cassandras +1
Traditional rebalancing methods in ride-hailing systems direct idle drivers to fixed destinations, overlooking the fact that ride allocations frequently occur while cruising. This…
Maximal Compatibility Matching for Preference-Aware Ride-Hailing Systems
Avalpreet Singh Brar, Rong Su, Jaskaranveer Kaur +2
This paper presents the Maximal Compatibility Matching (MCM) framework, a novel assignment strategy for ride-hailing systems that explicitly incorporates passenger comfort into the…
Robo-Taxi Fleet Coordination with Accelerated High-Capacity Ridepooling
Xinling Li, Daniele Gammelli, Alex Wallar +2
Rapid urbanization has led to a surge of customizable mobility demand in urban areas, which makes on-demand services increasingly popular. On-demand services are flexible while red…
Contact-Aware Safety in Soft Robots Using High-Order Control Barrier and Lyapunov Functions
Kiwan Wong, Maximilian Stölzle, Wei Xiao +3
Robots operating alongside people, particularly in sensitive scenarios such as aiding the elderly with daily tasks or collaborating with workers in manufacturing, must guarantee sa…
Soft yet Effective Robots via Holistic Co-Design
Maximilian Stölzle, Niccolò Pagliarani, Francesco Stella +6
Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Despite progress, the field struggles to balance t…
Robo-taxi Fleet Coordination at Scale via Reinforcement Learning
Luigi Tresca, Carolin Schmidt, James Harrison +4
Fleets of robo-taxis offering on-demand transportation services, commonly known as Autonomous Mobility-on-Demand (AMoD) systems, hold significant promise for societal benefits, suc…
CODEI: Resource-Efficient Task-Driven Co-Design of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles
Dejan Milojevic, Gioele Zardini, Miriam Elser +2
This paper discusses the integration challenges and strategies for designing mobile robots, by focusing on the task-driven, optimal selection of hardware and software to balance sa…
On Composable and Parametric Uncertainty in Systems Co-Design
Yujun Huang, Marius Furter, Gioele Zardini
Optimizing the design of complex systems requires navigating interdependent decisions, heterogeneous components, and multiple objectives. Our monotone theory of co-design offers a…
Iterative VCG-based Mechanism Fosters Cooperation in Multi-Regional Network Design
Mingjia He, Yannik Werner, Andrea Censi +2
Transportation network design often involves multiple stakeholders with diverse priorities. We consider a system with a hierarchical multi-agent structure, featuring self-optimized…
Composable Uncertainty in Symmetric Monoidal Categories for Design Problems (Extended Version)
Marius Furter, Yujun Huang, Gioele Zardini
Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, l…
User-Friendly Game-Theoretic Modeling and Analysis of Multi-Modal Transportation Systems
Margarita Zambrano, Xinling Li, Riccardo Fiorista +1
The evolution of existing transportation systems, mainly driven by urbanization and increased availability of mobility options, such as private, profit-maximizing ride-hailing comp…
FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness
Vincent Abbott, Gioele Zardini
Optimizing deep learning algorithms currently requires slow, manual derivation, potentially leaving much performance untapped. Methods like FlashAttention have achieved a x6 perfor…