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07/20/2023
Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks
Abstraction is a key verification technique to improve scalability. Howe...
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05/26/2023
MULTIGAIN 2.0: MDP controller synthesis for multiple mean-payoff, LTL and steady-state constraints
We present MULTIGAIN 2.0, a major extension to the controller synthesis ...
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05/24/2023
Guessing Winning Policies in LTL Synthesis by Semantic Learning
We provide a learning-based technique for guessing a winning strategy in...
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04/19/2023
Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectives
A classic solution technique for Markov decision processes (MDP) and sto...
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12/15/2022
Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks
Runtime monitoring provides a more realistic and applicable alternative ...
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08/26/2022
Algebraically Explainable Controllers: Decision Trees and Support Vector Machines Join Forces
Recently, decision trees (DT) have been used as an explainable represent...
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07/29/2022
Optimistic and Topological Value Iteration for Simple Stochastic Games
While value iteration (VI) is a standard solution approach to simple sto...
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07/27/2022
Satisfiability Bounds for ω-Regular Properties in Bounded-Parameter Markov Decision Processes
We consider the problem of computing minimum and maximum probabilities o...
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06/14/2022
Abstraction-Based Segmental Simulation of Chemical Reaction Networks
Simulating chemical reaction networks is often computationally demanding...
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06/03/2022
PAC Statistical Model Checking of Mean Payoff in Discrete- and Continuous-Time MDP
Markov decision processes (MDP) and continuous-time MDP (CTMDP) are the ...
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01/24/2022
Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processes
We introduce a similarity function on formulae of signal temporal logic ...
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05/31/2021
LTL-Constrained Steady-State Policy Synthesis
Decision-making policies for agents are often synthesized with the const...
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01/15/2021
dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts
Recent advances have shown how decision trees are apt data structures fo...
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09/23/2020
Comparison of Algorithms for Simple Stochastic Games
Simple stochastic games are turn-based 2.5-player zero-sum graph games w...
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08/21/2020
Comparison of Algorithms for Simple Stochastic Games (Full Version)
Simple stochastic games are turn-based 2.5-player zero-sum graph games w...
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06/30/2020
Formalizing and Guaranteeing* Human-Robot Interaction
Robot capabilities are maturing across domains, from self-driving cars, ...
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06/24/2020
DeepAbstract: Neural Network Abstraction for Accelerating Verification
While abstraction is a classic tool of verification to scale it up, it i...
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02/12/2020
dtControl: Decision Tree Learning Algorithms for Controller Representation
Decision tree learning is a popular classification technique most common...
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09/18/2019
Stopping Criteria for Value and Strategy Iteration on Concurrent Stochastic Reachability Games
We consider concurrent stochastic games played on graphs with reachabili...
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08/14/2019
Approximating Values of Generalized-Reachability Stochastic Games
Simple stochastic games are turn-based 2.5-player games with a reachabil...
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07/22/2019
Semantic Labelling and Learning for Parity Game Solving in LTL Synthesis
We propose "semantic labelling" as a novel ingredient for solving games ...
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06/25/2019
SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes
For hybrid Markov decision processes, UPPAAL Stratego can compute strate...
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06/19/2019
Strategy Representation by Decision Trees with Linear Classifiers
Graph games and Markov decision processes (MDPs) are standard models in ...
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06/17/2019
Of Cores: A Partial-Exploration Framework for Markov Decision Processes
We introduce a framework for approximate analysis of Markov decision pro...
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05/23/2019
Semi-Quantitative Abstraction and Analysis of Chemical Reaction Networks
Analysis of large continuous-time stochastic systems is a computationall...
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05/10/2019
PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games
Statistical model checking (SMC) is a technique for analysis of probabil...
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09/10/2018
Monte Carlo Tree Search for Verifying Reachability in Markov Decision Processes
The maximum reachability probabilities in a Markov decision process can ...
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07/25/2018
Continuous-Time Markov Decisions based on Partial Exploration
We provide a framework for speeding up algorithms for time-bounded reach...
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06/29/2018
LTL Store: Repository of LTL formulae from literature and case studies
This continuously extended technical report collects and compares common...
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06/29/2018
The Satisfiability Problem for Unbounded Fragments of Probabilistic CTL
We investigate the satisfiability and finite satisfiability problem for ...
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05/08/2018
Conditional Value-at-Risk for Reachability and Mean Payoff in Markov Decision Processes
We present the conditional value-at-risk (CVaR) in the context of Markov...
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05/02/2018
One Theorem to Rule Them All: A Unified Translation of LTL into ω-Automata
We present a unified translation of LTL formulas into deterministic Rabi...
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04/24/2018
Learning-Based Mean-Payoff Optimization in an Unknown MDP under Omega-Regular Constraints
We formalize the problem of maximizing the mean-payoff value with high p...
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04/13/2018
Value Iteration for Simple Stochastic Games: Stopping Criterion and Learning Algorithm
Simple stochastic games can be solved by value iteration (VI), which yie...
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02/02/2018
Strategy Representation by Decision Trees in Reactive Synthesis
Graph games played by two players over finite-state graphs are central i...
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07/06/2017
