mnist-guessnumber's Introduction

MNIST-GuessNumber Dataset

In the MNIST GuessNumber dataset, each sample consists of an image (left), a set of sequential questions with answers (right), and a target digit. The goal of this game is to find out the target digit through a multi-round question-answering.

Introduction:

This repository is based on Python3 and generates the MNIST-GuessNumber dataset.

The code was developed by Rui Zhao (Siemens AG & Ludwig Maximilian University of Munich).

The creation of MNIST-GuessNumber dataset is inspired by MNIST-Dialog dataset.

MNIST-GuessNumber dataset is a lightweight goal-oriented visual dialog testbed.

It is for quick test of Reinforcement Learning (RL) algorithms in dialog settings.

We designed this MNIST guess-number game and used it in our paper "Efficient Dialog Policy Learning via Positive Memory Retention".

The paper is published in 2018 IEEE Spoken Language Technology (SLT), link: https://ieeexplore.ieee.org/document/8639617.

The preprint version of the paper is avaliable at: https://arxiv.org/abs/1810.01371

This work was also presented at NIPS 2018 Visually Grounded Interaction and Language (ViGIL) Workshop.

Usage:

python generate_dataset.py

Then you can find the generated images and dialogs in the data folder :)

Citation:

Citation of the paper:

@inproceedings{zhao2018efficient,
  title={Efficient Dialog Policy Learning via Positive Memory Retention},
  author={Zhao, Rui and Tresp, Volker},
  booktitle={2018 IEEE Spoken Language Technology Workshop (SLT)},
  pages={823--830},
  year={2018},
  organization={IEEE}
}