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09/12/2023
A General Verification Framework for Dynamical and Control Models via Certificate Synthesis
An emerging branch of control theory specialises in certificate learning...
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07/28/2023
On the Trade-off Between Efficiency and Precision of Neural Abstraction
Neural abstractions have been recently introduced as formal approximatio...
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07/11/2023
On Imperfect Recall in Multi-Agent Influence Diagrams
Multi-agent influence diagrams (MAIDs) are a popular game-theoretic mode...
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06/05/2023
Networked Communication for Decentralised Agents in Mean-Field Games
We introduce networked communication to the mean-field game framework. I...
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03/30/2023
Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]
We introduce an adaptive refinement procedure for smart, and scalable ab...
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03/23/2023
Policy Evaluation in Distributional LQR
Distributional reinforcement learning (DRL) enhances the understanding o...
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02/27/2023
k-Prize Weighted Voting Games
We introduce a natural variant of weighted voting games, which we refer ...
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01/27/2023
Neural Abstractions
We present a novel method for the safety verification of nonlinear dynam...
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01/15/2023
Quantitative Verification With Neural Networks For Probabilistic Programs and Stochastic Systems
We present a machine learning approach to quantitative verification. We ...
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01/05/2023
Reasoning about Causality in Games
Causal reasoning and game-theoretic reasoning are fundamental topics in ...
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01/04/2023
Robust Control for Dynamical Systems With Non-Gaussian Noise via Formal Abstractions
Controllers for dynamical systems that operate in safety-critical settin...
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12/28/2022
Lexicographic Multi-Objective Reinforcement Learning
In this work we introduce reinforcement learning techniques for solving ...
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12/06/2022
Misspecification in Inverse Reinforcement Learning
The aim of Inverse Reinforcement Learning (IRL) is to infer a reward fun...
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12/01/2022
Formal Controller Synthesis for Markov Jump Linear Systems with Uncertain Dynamics
Automated synthesis of provably correct controllers for cyber-physical s...
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10/12/2022
Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty
Capturing uncertainty in models of complex dynamical systems is crucial ...
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09/30/2022
Observational Robustness and Invariances in Reinforcement Learning via Lexicographic Objectives
Policy robustness in Reinforcement Learning (RL) may not be desirable at...
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09/21/2022
LCRL: Certified Policy Synthesis via Logically-Constrained Reinforcement Learning
LCRL is a software tool that implements model-free Reinforcement Learnin...
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08/25/2022
Learning Task Automata for Reinforcement Learning using Hidden Markov Models
Training reinforcement learning (RL) agents using scalar reward signals ...
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08/12/2022
Low Emission Building Control with Zero-Shot Reinforcement Learning
Heating and cooling systems in buildings account for 31% of global energ...
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03/14/2022
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning
It's challenging to design reward functions for complex, real-world task...
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10/25/2021
Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise
Controllers for autonomous systems that operate in safety-critical setti...
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05/21/2021
Certification of Iterative Predictions in Bayesian Neural Networks
We consider the problem of computing reach-avoid probabilities for itera...
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04/29/2021
Grid-Free Computation of Probabilistic Safety with Malliavin Calculus
We work with continuous-time, continuous-space stochastic dynamical syst...
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02/24/2021
Modular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic
This paper investigates the motion planning of autonomous dynamical syst...
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02/09/2021
Equilibrium Refinements for Multi-Agent Influence Diagrams: Theory and Practice
Multi-agent influence diagrams (MAIDs) are a popular form of graphical m...
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02/01/2021
Multi-Agent Reinforcement Learning with Temporal Logic Specifications
In this paper, we study the problem of learning to satisfy temporal logi...
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01/19/2021
Automated Verification and Synthesis of Stochastic Hybrid Systems: A Survey
Stochastic hybrid systems have received significant attentions as a rele...
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08/07/2020
SafePILCO: a software tool for safe and data-efficient policy synthesis
SafePILCO is a software tool for safe and data-efficient policy search w...
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07/21/2020
Automated and Sound Synthesis of Lyapunov Functions with SMT Solvers
In this paper we employ SMT solvers to soundly synthesise Lyapunov funct...
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07/09/2020
Symbolic Reachability Analysis of High Dimensional Max-Plus Linear Systems
This work discusses the reachability analysis (RA) of Max-Plus Linear (M...
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07/07/2020
Automated Formal Synthesis of Neural Barrier Certificates for Dynamical Models
We introduce an automated, formal, counterexample-based approach to synt...
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07/06/2020
Jump Operator Planning: Goal-Conditioned Policy Ensembles and Zero-Shot Transfer
In Hierarchical Control, compositionality, abstraction, and task-transfe...
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07/01/2020
Computation of the Transient in Max-Plus Linear Systems via SMT-Solving
This paper proposes a new approach, grounded in Satisfiability Modulo Th...
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06/02/2020
Acceleration of Descent-based Optimization Algorithms via Carathéodory's Theorem
We propose a new technique to accelerate algorithms based on Gradient De...
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06/02/2020
A Randomized Algorithm to Reduce the Support of Discrete Measures
Given a discrete probability measure supported on N atoms and a set of n...
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04/23/2020
Bayesian Verification of Chemical Reaction Networks
We present a data-driven verification approach that determines whether o...
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03/19/2020
Automated Formal Synthesis of Lyapunov Neural Networks
We propose an automated and sound technique to synthesize provably corre...
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02/26/2020
Cautious Reinforcement Learning with Logical Constraints
This paper presents the concept of an adaptive safe padding that forces ...
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11/29/2019
Safety Guarantees for Planning Based on Iterative Gaussian Processes
Gaussian Processes (GPs) are widely employed in control and learning bec...
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11/22/2019
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning
We propose a method for effective training of deep Reinforcement Learnin...
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11/22/2019
DeepSynth: Program Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning
We propose a method for efficient training of deep Reinforcement Learnin...
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09/23/2019
Modular Deep Reinforcement Learning with Temporal Logic Specifications
We propose an actor-critic, model-free, and online Reinforcement Learnin...
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09/17/2019
Verifying Reachability Properties in Markov Chains via Incremental Induction
There is a scalability gap between probabilistic and non-probabilistic v...
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09/11/2019
Reinforcement Learning for Temporal Logic Control Synthesis with Probabilistic Satisfaction Guarantees
Reinforcement Learning (RL) has emerged as an efficient method of choice...
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07/08/2019
Bounded Model Checking of Max-Plus Linear Systems via Predicate Abstractions
This paper introduces the abstraction of max-plus linear (MPL) systems v...
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02/02/2019
Certified Reinforcement Learning with Logic Guidance
This paper proposes the first model-free Reinforcement Learning (RL) fra...
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09/20/2018
Logically-Constrained Neural Fitted Q-Iteration
This paper proposes a method for efficient training of the Q-function fo...
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01/24/2018
Logically-Correct Reinforcement Learning
We propose a novel Reinforcement Learning (RL) algorithm to synthesize p...
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01/12/2018
Efficient Probabilistic Model Checking of Smart Building Maintenance using Fault Maintenance Trees
Cyber-physical systems, like Smart Buildings and power plants, have to m...
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12/20/2017
