Statistical Model Checking

Latest papers

8 papers2 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Micro Neural Policies for Safe Real-Time Robotic Control
Oct 6, 2026Hongpeng Cao, Riccardo Curcio, Daniele Ottaviano +1Robotic Control Statistical Model Checking
School of Engineering and Design, Technical University of Munich, Boltzmannstraße 15, 85748 Garching b. München, Germany · Department of Computer Science, Sapienza University of Rome, Via Salaria 113, 00198 Rome, Italy
Scenario-Based Compositional Statistical Model Checking for Safety Specifications
Oct 4, 2026Abhinav Pomalapally, Arya Raeesi, Kevin Kai-Chun Chang +2Statistical Model Checking Formal Verification
University of California, Berkeley, USA
LyEvO: Lyapunov-Guided Evolutionary Optimization for Safe and Robust Sim-to-Real Policy Learning
Aug 6, 2026Riccardo Curcio, Hongpeng Cao, Marco CaccamoRobot Policy Learning Evolutionary Optimization
Department of Computer Science, Sapienza University of Rome, via Salaria 113, 00198 Rome, Italy · School of Engineering and Design, Technical University of Munich, Boltzmannstraße 15, 85748 Garching b. München, Germany
SMC-ES: Automated synthesis of formally verified control policies
Jul 16, 2026Riccardo Curcio, Toni Mancini, Enrico TronciStatistical Model Checking Formal Verification
Department of Computer Science, Sapienza University of Rome, via Salaria 113, 00198 Rome, Italy
Confidence Sequences for Online Statistical Model Checking of Markov Decision Processes
Jun 24, 2026Konstantin Kueffner, Tobias Meggendorfer, Maximilian Weininger +1Markov Decision Processes Uncertainty Quantification
Institute of Science and Technology Austria, Klosterneuburg, Austria · Lancaster University Leipzig, Leipzig, Germany · Ruhr-University Bochum, Bochum, Germany +1
Statistical Model Checking of the Keynes+Schumpeter Model: A Transient Sensitivity Analysis of a Macroeconomic ABM
May 11, 2026Stefano Blando, Giorgio Fagiolo, Mauro Napoletano +2Statistical Model Checking Agent-Based Modeling
Institute of Economics and L’EMbeDS2026 Sant’Anna School of Advanced Studies, Pisa, Italy · GREDEG, CNRS, Université Côte d’Azur Sophia Antipolis, France · Maastricht University Maastricht, The Netherlands
Statistical Model Checking of the Island Model: An Established Economic Agent-Based Model of Endogenous Growth
Apr 6, 2026Stefano Blando, Giorgio Fagiolo, Daniele Giachini +2Statistical Model Checking Agent-Based Modeling
Institute of Economics and L'EMbeDS, Sant'Anna School of Advanced Studies · Institute of Economics and L’EMbeDS, Sant’Anna School of Advanced Studies, Pisa, Italy · Swiss Finance Institute and University of Geneve +1
The SCAN Statistical Model Checker
Mar 24, 2026Enrico Ghiorzi, Armando TacchellaStatistical Model Checking Formal Verification
Università di Genova

Oct 6, 2026J/K move · Enter open · S save

Micro Neural Policies for Safe Real-Time Robotic Control

Hongpeng Cao, Riccardo Curcio, Daniele Ottaviano, Marco Caccamo

School of Engineering and Design, Technical University of Munich, Boltzmannstraße 15, 85748 Garching b. München, Germany · Department of Computer Science, Sapienza University of Rome, Via Salaria 113, 00198 Rome, Italy

Robotic Control Statistical Model Checking Robot Safety

Open paper AskPDF arXiv

In this paper, we investigate the synthesis of Micro Neural Policies (MNP) to enable safe and robust real-time robotic control on computationally constrained embedded devices. We demonstrate that integrating Evolution Strategy (ES) and Statistical Model Checking (SMC)-based verification for policy search can drastically reduce neural network size without compromising safety and robustness. We conduct a large-scale training and evaluation of MNP on Cartpole and Quadrotor control tasks, varying control frequencies and network architectures. After validating these policies in simulation, we evaluate their deployability through zero-shot transfer to physical systems. Our experiments show that MNP can successfully achieve safe sim-to-real transfer without sacrificing control performance. We then show that the policies' memory footprint, ranging from 0.5 to 7.5 kB, allows deployment on microcontrollers, where they achieve real-time inference latency with under 25 ns of jitter while leaving the chip idle for over 97% of the time for additional workloads. This makes them a highly practical solution for severely resource-constrained robotic systems.