research
∙
07/19/2023
Learning Formal Specifications from Membership and Preference Queries
Active learning is a well-studied approach to learning formal specificat...
share
research
∙
12/20/2021
Demonstration Informed Specification Search
This paper considers the problem of learning history dependent task spec...
research
∙
05/26/2021
Model Checking Finite-Horizon Markov Chains with Probabilistic Inference
We revisit the symbolic verification of Markov chains with respect to fi...
research
∙
03/09/2021
Entropy-Guided Control Improvisation
High level declarative constraints provide a powerful (and popular) way ...
research
∙
07/26/2019
Learning Task Specifications from Demonstrations via the Principle of Maximum Causal Entropy
In many settings (e.g., robotics) demonstrations provide a natural way t...
research
∙
07/24/2019
Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques
Cyber-physical system applications such as autonomous vehicles, wearable...
research
∙
03/22/2019
A Model Counter's Guide to Probabilistic Systems
In this paper, we systematize the modeling of probabilistic systems for ...
research
∙
02/12/2019
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
We present VERIFAI, a software toolkit for the formal design and analysi...
research
∙
02/24/2018
Time Series Learning using Monotonic Logical Properties
We propose a new paradigm for time-series learning where users implicitl...
research
∙
10/11/2017
