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08/14/2023
Omega-Regular Reward Machines
Reinforcement learning (RL) is a powerful approach for training agents t...
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05/27/2023
Closure Certificates
A barrier certificate, defined over the states of a dynamical system, is...
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05/26/2023
Policy Synthesis and Reinforcement Learning for Discounted LTL
The difficulty of manually specifying reward functions has led to an int...
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04/09/2023
Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks
The deep feedforward neural networks (DNNs) are increasingly deployed in...
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03/16/2023
Reinforcement Learning for Omega-Regular Specifications on Continuous-Time MDP
Continuous-time Markov decision processes (CTMDPs) are canonical models ...
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02/27/2023
Reinforcement Learning with Depreciating Assets
A basic assumption of traditional reinforcement learning is that the val...
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06/23/2022
Recursive Reinforcement Learning
Recursion is the fundamental paradigm to finitely describe potentially i...
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05/10/2022
Metamorphic Testing and Debugging of Tax Preparation Software
This paper presents a data-driven debugging framework to improve the tru...
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05/06/2022
Alternating Good-for-MDP Automata
When omega-regular objectives were first proposed in model-free reinforc...
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02/14/2022
Secure-by-Construction Synthesis of Cyber-Physical Systems
Correct-by-construction synthesis is a cornerstone of the confluence of ...
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08/18/2021
Selectively-Amortized Resource Bounding (Extended Version)
We consider the problem of automatically proving resource bounds. That i...
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07/09/2021
Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes
The success of reinforcement learning in typical settings is, in part, p...
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06/16/2021
Mungojerrie: Reinforcement Learning of Linear-Time Objectives
Reinforcement learning synthesizes controllers without prior knowledge o...
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06/12/2021
Model-free Reinforcement Learning for Branching Markov Decision Processes
We study reinforcement learning for the optimal control of Branching Mar...
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06/05/2021
Controller Synthesis for Omega-Regular and Steady-State Specifications
Given a Markov decision process (MDP) and a linear-time (ω-regular or LT...
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02/13/2021
Discounting the Past in Stochastic Games
Stochastic games, introduced by Shapley, model adversarial interactions ...
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06/03/2020
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries
Programming errors that degrade the performance of systems are widesprea...
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03/02/2020
Formal Controller Synthesis for Continuous-Space MDPs via Model-Free Reinforcement Learning
A novel reinforcement learning scheme to synthesize policies for continu...
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10/20/2019
MSO-Definable Regular Model Checking
Regular Model Checking (RMC) is a symbolic model checking technique wher...
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07/23/2019
Efficient Detection and Quantification of Timing Leaks with Neural Networks
Detection and quantification of information leaks through timing side ch...
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06/21/2019
Quantitative Mitigation of Timing Side Channels
Timing side channels pose a significant threat to the security and priva...
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10/24/2018
Type-directed Bounding of Collections in Reactive Programs
Our aim is to statically verify that in a given reactive program, the le...
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09/26/2018
Omega-Regular Objectives in Model-Free Reinforcement Learning
We provide the first solution for model-free reinforcement learning of ω...
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08/30/2018
Data-Driven Debugging for Functional Side Channels
Functional side channels arise when an attacker knows that the secret va...
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11/11/2017
Differential Performance Debugging with Discriminant Regression Trees
Differential performance debugging is a technique to find performance pr...
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12/13/2016