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09/18/2023
Specification-Driven Video Search via Foundation Models and Formal Verification
The increasing abundance of video data enables users to search for event...
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09/09/2023
Verifiable Reinforcement Learning Systems via Compositionality
We propose a framework for verifiable and compositional reinforcement le...
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08/15/2023
Active Inverse Learning in Stackelberg Trajectory Games
Game-theoretic inverse learning is the problem of inferring the players'...
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08/10/2023
Multimodal Pretrained Models for Sequential Decision-Making: Synthesis, Verification, Grounding, and Perception
Recently developed pretrained models can encode rich world knowledge exp...
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06/23/2023
Reinforcement Learning with Temporal-Logic-Based Causal Diagrams
We study a class of reinforcement learning (RL) tasks where the objectiv...
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06/10/2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations
We present a framework and algorithms to learn controlled dynamics model...
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06/10/2023
Autonomous Drifting with 3 Minutes of Data via Learned Tire Models
Near the limits of adhesion, the forces generated by a tire are nonlinea...
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05/27/2023
Reinforcement Learning With Reward Machines in Stochastic Games
We investigate multi-agent reinforcement learning for stochastic games w...
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05/25/2023
Reward-Machine-Guided, Self-Paced Reinforcement Learning
Self-paced reinforcement learning (RL) aims to improve the data efficien...
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05/24/2023
Task-aware Distributed Source Coding under Dynamic Bandwidth
Efficient compression of correlated data is essential to minimize commun...
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05/01/2023
Efficient Sensitivity Analysis for Parametric Robust Markov Chains
We provide a novel method for sensitivity analysis of parametric robust ...
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03/31/2023
Soft-Bellman Equilibrium in Affine Markov Games: Forward Solutions and Inverse Learning
Markov games model interactions among multiple players in a stochastic, ...
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03/07/2023
On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples
Offline reinforcement learning (offline RL) considers problems where lea...
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02/28/2023
Learning Sparse Control Tasks from Pixels by Latent Nearest-Neighbor-Guided Explorations
Recent progress in deep reinforcement learning (RL) and computer vision ...
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01/20/2023
Differential Privacy in Cooperative Multiagent Planning
Privacy-aware multiagent systems must protect agents' sensitive data whi...
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01/09/2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
Data-driven control algorithms use observations of system dynamics to co...
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12/30/2022
Task-Guided IRL in POMDPs that Scales
In inverse reinforcement learning (IRL), a learning agent infers a rewar...
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12/04/2022
Learning Automata-Based Task Knowledge Representation from Large-Scale Generative Language Models
Automata-based representations play an important role in control and pla...
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12/02/2022
Learning Temporal Logic Properties: an Overview of Two Recent Methods
Learning linear temporal logic (LTL) formulas from examples labeled as p...
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12/01/2022
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks
Many dynamical systems – from robots interacting with their surroundings...
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11/21/2022
Sensor Placement for Online Fault Diagnosis
Fault diagnosis is the problem of determining a set of faulty system com...
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10/03/2022
Cost Design in Atomic Routing Games
An atomic routing game is a multiplayer game on a directed graph. Each p...
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09/09/2022
Alternating Direction Method of Multipliers for Decomposable Saddle-Point Problems
Saddle-point problems appear in various settings including machine learn...
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09/06/2022
Learning Interpretable Temporal Properties from Positive Examples Only
We consider the problem of explaining the temporal behavior of black-box...
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08/29/2022
Categorical semantics of compositional reinforcement learning
Reinforcement learning (RL) often requires decomposing a problem into su...
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07/17/2022
Inverse Matrix Games with Unique Quantal Response Equilibrium
In an inverse game problem, one needs to infer the cost function of the ...
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07/13/2022
Relationship Design for Socially Desirable Behavior in Static Games
Interactions among multiple self-interested agents may not necessarily y...
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06/02/2022
Deceptive Planning for Resource Allocation
We consider a team of autonomous agents that navigate in an adversarial ...
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05/25/2022
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning
We study the privacy risks that are associated with training a neural ne...
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04/27/2022
Hierarchical Control for Cooperative Teams in Competitive Autonomous Racing
We study the problem of autonomous racing amongst teams composed of coop...
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04/20/2022
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics
We study the problem of reinforcement learning for a task encoded by a r...
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04/02/2022
Safe Reinforcement Learning via Shielding for POMDPs
Reinforcement learning (RL) in safety-critical environments requires an ...
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03/21/2022
Dynamic Certification for Autonomous Systems
Autonomous systems are often deployed in complex sociotechnical environm...
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03/05/2022
Safely: Safe Stochastic Motion Planning Under Constrained Sensing via Duality
Consider a robot operating in an uncertain environment with stochastic, ...
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03/03/2022
AlgebraicSystems: Compositional Verification for Autonomous System Design
Autonomous systems require the management of several model views to assu...
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02/25/2022
Hierarchical Control for Multi-Agent Autonomous Racing
We develop a hierarchical controller for multi-agent autonomous racing. ...
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02/10/2022
No-Regret Learning in Dynamic Stackelberg Games
In a Stackelberg game, a leader commits to a randomized strategy, and a ...
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01/26/2022
Class-Aware Generative Adversarial Transformers for Medical Image Segmentation
Transformers have made remarkable progress towards modeling long-range d...
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01/17/2022
Planning Not to Talk: Multiagent Systems that are Robust to Communication Loss
In a cooperative multiagent system, a collection of agents executes a jo...
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01/14/2022
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs
Neural ordinary differential equations (NODEs) – parametrizations of dif...
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12/24/2021
Scenario-Based Verification of Uncertain Parametric MDPs
We consider parametric Markov decision processes (pMDPs) that are augmen...
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12/01/2021
A Barrier Pair Method for Safe Human-Robot Shared Autonomy
Shared autonomy provides a framework where a human and an automated syst...
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10/11/2021
Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systems
We develop a learning-based algorithm for the distributed formation cont...
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10/06/2021
On The Vulnerability of Recurrent Neural Networks to Membership Inference Attacks
We study the privacy implications of deploying recurrent neural networks...
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09/17/2021
Adapting to the Behavior of Environments with Bounded Memory
We study the problem of synthesizing implementations from temporal logic...
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09/14/2021
Deceptive Decision-Making Under Uncertainty
We study the design of autonomous agents that are capable of deceiving o...
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09/14/2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
Effective inclusion of physics-based knowledge into deep neural network ...
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09/10/2021
Simultaneous Perception-Action Design via Invariant Finite Belief Sets
Although perception is an increasingly dominant portion of the overall c...
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08/22/2021
From Agile Ground to Aerial Navigation: Learning from Learned Hallucination
This paper presents a self-supervised Learning from Learned Hallucinatio...
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06/30/2021