# Towards End-to-End Learning for Dialog State Tracking and Management using Deep Reinforcement Learning

arXiv: https://arxiv.org/abs/1606.02560 · HTML: https://mlsanity.com/paper/1606.02560/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jun 2016.

## Built on by (most cited first, 29 of 29)

- [A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://mlsanity.com/paper/2402.18013/) (2024)
- [Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey](https://mlsanity.com/paper/2105.04387/) (2021)
- [A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-Oriented Dialogue Policy Learning](https://mlsanity.com/paper/2202.13675/) (2022)
- [ChatShop: Interactive Information Seeking with Language Agents](https://mlsanity.com/paper/2404.09911/) (2024)
- [Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning](https://mlsanity.com/paper/1801.06176/) (2018)
- [A Survey on Deep Reinforcement Learning for Audio-Based Applications](https://mlsanity.com/paper/2101.00240/) (2021)
- [End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions](https://mlsanity.com/paper/2311.09008/) (2023)
- [Long-Horizon Dialogue Understanding for Role Identification in the Game of Avalon with Large Language Models](https://mlsanity.com/paper/2311.05720/) (2023)
- [Reinforcement Learning for Generative AI: A Survey](https://mlsanity.com/paper/2308.14328/) (2023)
- [A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback](https://mlsanity.com/paper/2411.13410/) (2024)
- [Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning](https://mlsanity.com/paper/2509.15188/) (2025)
- [Post-processing Networks: Method for Optimizing Pipeline Task-oriented Dialogue Systems using Reinforcement Learning](https://mlsanity.com/paper/2207.12185/) (2022)
- [Using Textual Interface to Align External Knowledge for End-to-End Task-Oriented Dialogue Systems](https://mlsanity.com/paper/2305.13710/) (2023)
- [Are Current Task-oriented Dialogue Systems Able to Satisfy Impolite Users?](https://mlsanity.com/paper/2210.12942/) (2022)
- [A Deep Reinforcement Learning Approach for Traffic Signal Control Optimization](https://mlsanity.com/paper/2107.06115/) (2021)
- [WeaSuL: Weakly Supervised Dialogue Policy Learning: Reward Estimation for Multi-turn Dialogue](https://mlsanity.com/paper/2108.01487/) (2021)
- [A Speaker-aware Parallel Hierarchical Attentive Encoder-Decoder Model for Multi-turn Dialogue Generation](https://mlsanity.com/paper/2110.06823/) (2021)
- [End-to-End Evaluation of a Spoken Dialogue System for Learning Basic Mathematics](https://mlsanity.com/paper/2211.03511/) (2022)
- [Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue](https://mlsanity.com/paper/2102.02435/) (2021)
- [DRL: Deep Reinforcement Learning for Intelligent Robot Control -- Concept, Literature, and Future](https://mlsanity.com/paper/2105.13806/) (2021)
- [Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System](https://mlsanity.com/paper/2106.04835/) (2021)
- [Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems](https://mlsanity.com/paper/2110.05221/) (2021)
- [A Spoken Drug Prescription Dataset in French for Spoken Language Understanding](https://mlsanity.com/paper/2207.08292/) (2022)
- [Every time I fire a conversational designer, the performance of the dialog system goes down](https://mlsanity.com/paper/2109.13029/) (2021)
- [Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases](https://mlsanity.com/paper/2203.14144/) (2022)
- [Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings](https://mlsanity.com/paper/2207.00468/) (2022)
- [Spoken Dialogue System for Medical Prescription Acquisition on Smartphone: Development, Corpus and Evaluation](https://mlsanity.com/paper/2311.03510/) (2023)
- [Optimizing Conversational Product Recommendation via Reinforcement Learning](https://mlsanity.com/paper/2507.01060/) (2025)
- [Dont Just Teach, Explain! A Gamified 20Q Recommender for Cybersecurity Education](https://mlsanity.com/paper/2604.26964/) (2026)

## Abstract (arXiv)

This paper presents an end-to-end framework for task-oriented dialog systems using a variant of Deep Recurrent Q-Networks (DRQN). The model is able to interface with a relational database and jointly learn policies for both language understanding and dialog strategy. Moreover, we propose a hybrid algorithm that combines the strength of reinforcement learning and supervised learning to achieve faster learning speed. We evaluated the proposed model on a 20 Question Game conversational game simulator. Results show that the proposed method outperforms the modular-based baseline and learns a distributed representation of the latent dialog state.