Inferring Temporal Logic Properties from Data using Boosted Decision Trees

05/24/2021
by   Erfan Aasi, et al.
0

Many autonomous systems, such as robots and self-driving cars, involve real-time decision making in complex environments, and require prediction of future outcomes from limited data. Moreover, their decisions are increasingly required to be interpretable to humans for safe and trustworthy co-existence. This paper is a first step towards interpretable learning-based robot control. We introduce a novel learning problem, called incremental formula and predictor learning, to generate binary classifiers with temporal logic structure from time-series data. The classifiers are represented as pairs of Signal Temporal Logic (STL) formulae and predictors for their satisfaction. The incremental property provides prediction of labels for prefix signals that are revealed over time. We propose a boosted decision-tree algorithm that leverages weak, but computationally inexpensive, learners to increase prediction and runtime performance. The effectiveness and classification accuracy of our algorithms are evaluated on autonomous-driving and naval surveillance case studies.

READ FULL TEXT

Authors

page 2

10/01/2021

Classification of Time-Series Data Using Boosted Decision Trees

Time-series data classification is central to the analysis and control o...
12/28/2021

Time-Incremental Learning from Data Using Temporal Logics

Real-time and human-interpretable decision-making in cyber-physical syst...
07/24/2019

Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques

Cyber-physical system applications such as autonomous vehicles, wearable...
06/16/2021

Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems

The Internet-of-Things, complex sensor networks, multi-agent cyber-physi...
03/07/2020

Prediction with Spatio-temporal Point Processes with Self Organizing Decision Trees

We study the spatio-temporal prediction problem, which has attracted att...
11/13/2017

A Robust Genetic Algorithm for Learning Temporal Specifications from Data

We consider the problem of mining signal temporal logical requirements f...
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 ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.