swMATH ID: 32550
Software Authors: Tommaso Dreossi, Daniel J. Fremont, Shromona Ghosh, Edward Kim, Hadi Ravanbakhsh, Marcell Vazquez-Chanlatte, Sanjit A. Seshia
Description: VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems. We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particularly seeks to address challenges with applying formal methods to perception and ML components, including those based on neural networks, and to model and analyze system behavior in the presence of environment uncertainty. We describe the initial version of VERIFAI which centers on simulation guided by formal models and specifications. Several use cases are illustrated with examples, including temporal-logic falsification, model-based systematic fuzz testing, parameter synthesis, counterexample analysis, and data set augmentation.
Homepage: https://arxiv.org/abs/1902.04245
Source Code:  https://github.com/BerkeleyLearnVerify/VerifAI
Keywords: Artificial Intelligence; arXiv_cs.AI
Related Software: Reluplex; NNV; Marabou; MNIST; SqueezeDet; Easychair; MPT; HYST; CORA; Model Predictive Control Toolbox; ReachNN; TensorFlow Quantum; Adam; TensorFlow; CVXPY; nncontroller; Safety Gym; HSolver; Benchmarks; RSOLVER
Cited in: 3 Documents

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