b'Ufuk Topcu'

research

∙ 07/17/2022

Inverse Matrix Games with Unique Nash Equilibrium

In an inverse game problem, one needs to infer the cost function of the ...

Yue Yu, et al. ∙

research

∙ 07/13/2022

Relationship Design for Socially Desirable Behavior in Static Games

Interactions among multiple self-interested agents may not necessarily y...

Shenghui Chen, et al. ∙

research

∙ 06/02/2022

Deceptive Planning for Resource Allocation

We consider a team of autonomous agents that navigate in an adversarial ...

Yagiz Savas, et al. ∙

research

∙ 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...

Yunhao Yang, et al. ∙

research

∙ 04/27/2022

Hierarchical Control for Cooperative Teams in Competitive Autonomous Racing

We study the problem of autonomous racing amongst teams composed of coop...

Rishabh Saumil Thakkar, et al. ∙

research

∙ 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...

Christos Verginis, et al. ∙

research

∙ 04/02/2022

Safe Reinforcement Learning via Shielding for POMDPs

Reinforcement learning (RL) in safety-critical environments requires an ...

Steven Carr, et al. ∙

research

∙ 03/21/2022

Dynamic Certification for Autonomous Systems

Autonomous systems are often deployed in complex sociotechnical environm...

Georgios Bakirtzis, et al. ∙

research

∙ 03/05/2022

Safely: Safe Stochastic Motion Planning Under Constrained Sensing via Duality

Consider a robot operating in an uncertain environment with stochastic, ...

Michael Hibbard, et al. ∙

research

∙ 03/03/2022

AlgebraicSystems: Compositional Verification for Autonomous System Design

Autonomous systems require the management of several model views to assu...

Georgios Bakirtzis, et al. ∙

research

∙ 02/25/2022

Hierarchical Control for Multi-Agent Autonomous Racing

We develop a hierarchical controller for multi-agent autonomous racing. ...

Rishabh Saumil Thakkar, et al. ∙

research

∙ 02/10/2022

No-Regret Learning in Dynamic Stackelberg Games

In a Stackelberg game, a leader commits to a randomized strategy, and a ...

Niklas Lauffer, et al. ∙

research

∙ 01/26/2022

Class-Aware Generative Adversarial Transformers for Medical Image Segmentation

Transformers have made remarkable progress towards modeling long-range d...

Chenyu You, et al. ∙

research

∙ 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...

Mustafa O. Karabag, et al. ∙

research

∙ 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...

Franck Djeumou, et al. ∙

research

∙ 12/24/2021

Scenario-Based Verification of Uncertain Parametric MDPs

We consider parametric Markov decision processes (pMDPs) that are augmen...

Thom S. Badings, et al. ∙

research

∙ 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...

Binghan He, et al. ∙

research

∙ 10/11/2021

Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systems

We develop a learning-based algorithm for the distributed formation cont...

Christos K. Verginis, et al. ∙

research

∙ 10/06/2021

On The Vulnerability of Recurrent Neural Networks to Membership Inference Attacks

We study the privacy implications of deploying recurrent neural networks...

Yunhao Yang, et al. ∙

research

∙ 09/17/2021

Adapting to the Behavior of Environments with Bounded Memory

We study the problem of synthesizing implementations from temporal logic...

Dhananjay Raju, et al. ∙

research

∙ 09/14/2021

Deceptive Decision-Making Under Uncertainty

We study the design of autonomous agents that are capable of deceiving o...

Yagiz Savas, et al. ∙

research

∙ 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 ...

Franck Djeumou, et al. ∙

research

∙ 09/10/2021

Simultaneous Perception-Action Design via Invariant Finite Belief Sets

Although perception is an increasingly dominant portion of the overall c...

Michael Hibbard, et al. ∙

research

∙ 08/22/2021

From Agile Ground to Aerial Navigation: Learning from Learned Hallucination

This paper presents a self-supervised Learning from Learned Hallucinatio...

Zizhao Wang, et al. ∙

research

∙ 06/30/2021

Robust Generative Adversarial Imitation Learning via Local Lipschitzness

We explore methodologies to improve the robustness of generative adversa...

Farzan Memarian, et al. ∙

research

∙ 06/30/2021

Convex Optimization for Parameter Synthesis in MDPs

Probabilistic model checking aims to prove whether a Markov decision pro...

Murat Cubuktepe, et al. ∙

research

∙ 06/29/2021

Probabilistic Control of Heterogeneous Swarms Subject to Graph Temporal Logic Specifications: A Decentralized and Scalable Approach

We develop a probabilistic control algorithm, , for swarms of agents wit...

Franck Djeumou, et al. ∙

research

∙ 06/25/2021

Non-Parametric Neuro-Adaptive Control Subject to Task Specifications

We develop a learning-based algorithm for the control of robotic systems...

Christos K. Verginis, et al. ∙

research

∙ 06/19/2021

Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information

We develop a learning-based control algorithm for unknown dynamical syst...

Franck Djeumou, et al. ∙

research

∙ 06/16/2021

Robust Training in High Dimensions via Block Coordinate Geometric Median Descent

Geometric median (Gm) is a classical method in statistics for achieving ...

Anish Acharya, et al. ∙

research

∙ 06/07/2021

Verifiable and Compositional Reinforcement Learning Systems

We propose a novel framework for verifiable and compositional reinforcem...

Cyrus Neary, et al. ∙

research

∙ 05/28/2021

Task-Guided Inverse Reinforcement Learning Under Partial Information

We study the problem of inverse reinforcement learning (IRL), where the ...

Franck Djeumou, et al. ∙

research

∙ 05/24/2021

Uncertainty-Aware Signal Temporal Logic Inference

Temporal logic inference is the process of extracting formal description...

Nasim Baharisangari, et al. ∙

research

∙ 05/12/2021

Identity Concealment Games: How I Learned to Stop Revealing and Love the Coincidences

In an adversarial environment, a hostile player performing a task may be...

Mustafa O. Karabag, et al. ∙

research

∙ 05/05/2021

Efficient Strategy Synthesis for MDPs with Resource Constraints

We consider qualitative strategy synthesis for the formalism called cons...

František Blahoudek, et al. ∙

research

∙ 05/04/2021

Polynomial-Time Algorithms for Multi-Agent Minimal-Capacity Planning

We study the problem of minimizing the resource capacity of autonomous a...

Murat Cubuktepe, et al. ∙

research

∙ 04/30/2021

Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach

We address the problem of inferring descriptions of system behavior usin...

Jean-Raphaël Gaglione, et al. ∙

research

∙ 03/08/2021

Self-Supervised Online Reward Shaping in Sparse-Reward Environments

We propose a novel reinforcement learning framework that performs self-s...

Farzan Memarian, et al. ∙

research

∙ 03/04/2021

Function Approximation via Sparse Random Features

Random feature methods have been successful in various machine learning ...

Abolfazl Hashemi, et al. ∙

research

∙ 03/02/2021

A 3D Printing Hexacopter: Design and Demonstration

3D printing using robots has garnered significant interest in manufactur...

Alexander Nettekoven, et al. ∙

research

∙ 01/27/2021

Safe Multi-Agent Reinforcement Learning via Shielding

Multi-agent reinforcement learning (MARL) has been increasingly used in ...

Ingy Elsayed-Aly, et al. ∙

research

∙ 12/31/2020

Multiple Plans are Better than One: Diverse Stochastic Planning

In planning problems, it is often challenging to fully model the desired...

Mahsa Ghasemi, et al. ∙

research

∙ 11/18/2020

Towards online monitoring and data-driven control: a study of segmentation algorithms for infrared images of the powder bed

An increasing number of selective laser sintering and selective laser me...

Alexander Nettekoven, et al. ∙

research

∙ 10/27/2020

Assured Autonomy: Path Toward Living With Autonomous Systems We Can Trust

The challenge of establishing assurance in autonomy is rapidly attractin...

Ufuk Topcu, et al. ∙

research

∙ 09/24/2020

Minimum-Violation Planning for Autonomous Systems: Theoretical and Practical Considerations

This paper considers the problem of computing an optimal trajectory for ...

Tichakorn Wongpiromsarn, et al. ∙

research

∙ 09/24/2020

Robust Finite-State Controllers for Uncertain POMDPs

Uncertain partially observable Markov decision processes (uPOMDPs) allow...

Murat Cubuktepe, et al. ∙

research

∙ 09/05/2020

BP-RRT: Barrier Pair Synthesis for Temporal Logic Motion Planning

For a nonlinear system (e.g. a robot) with its continuous state space tr...

Binghan He, et al. ∙

research

∙ 07/31/2020

Near-Optimal Reactive Synthesis Incorporating Runtime Information

We consider the problem of optimal reactive synthesis - compute a strate...

Suda Bharadwaj, et al. ∙

research

∙ 06/25/2020

Distributed Policy Synthesis of Multi-Agent Systems With Graph Temporal Logic Specifications

We study the distributed synthesis of policies for multi-agent systems t...

Murat Cubuktepe, et al. ∙

research

∙ 05/14/2020

Qualitative Controller Synthesis for Consumption Markov Decision Processes

Consumption Markov Decision Processes (CMDPs) are probabilistic decision...

František Blahoudek, et al. ∙

Ufuk Topcu

Featured Co-authors