Abstract: In this article, we introduce a novel framework that combines constraint logic programming (CLP) with deep reinforcement learning (DRL) to create adaptive environments for continual learning ...
Abstract: Signal Temporal Logic (STL) provides a convenient way of encoding complex control objectives for robotic and cyber-physical systems. The state-of-the-art in trajectory synthesis for STL is ...
This repository contains a maintained and modernized version of the Espresso logic minimizer, originally developed at the University of California, Berkeley. Espresso is a heuristic multi-valued PLA ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results