Train RNNs to recognize regular languages.
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Updated
May 19, 2023 - Python
Train RNNs to recognize regular languages.
Implementation of the L* (L Star) based Assume Guarantee Reasoning framework - dynamic DFA input as specification
Explore Aksara Jawa effortlessly with YOLOv8 and Finite State Automata-powered Transliteration that i developed. Achieving high metrics (Train: 0.967/0.922/0.961, Validation: 0.966/0.924/0.961), our Streamlit interface ensures easy input and accurate output. Unlock precision and simplicity in Aksara Jawa to Latin conversion.
Grammatical inference using the Z3 SMT solver
Enabling Model-Based Diagnosis and Failure Model Generation with Active Automata Learning
This project provides a strategy for converting a CFG "If-Else" condition selection that is compatible with both Go and Python programming languages.
🏆 时间自动机模型学习工具站点(Timed Automata)
Black-box extraction of Finite-State Machines from RNNs.
This repository contains an implementation of DISC, an algorithm for learning DFAs for multiclass sequence classification.
An automata learning library written in Python.
Code for the papers "Induction of Subgoal Automata for Reinforcement Learning" (AAAI-20) and "Induction and Exploitation of Subgoal Automata for Reinforcement Learning" (JAIR).
An Automata Learning Library Written in Python
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