### oral presentation
1. **CAUSAL DISCOVERY WITH REINFORCEMENT LEARNING** ICLR 2020. [paper](https://arxiv.org/pdf/1906.04477.pdf)

    *Shengyu Zhu, Ignavier Ng, Zhitang Chen*

2. **Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect informatio** ICLR 2020. [paper](https://openreview.net/pdf?id=Syg-ET4FPS)

    *Yichi Zhou , Jialian Li, Jun Zhu*
    
3. **Harnessing Structures for Value-Based Planning and Reinforcement Learning** ICLR2020. [paper](https://arxiv.org/pdf/1909.12255.pdf)

    *Yuzhe Yang , Guo Zhang, Zhi Xu, Dina Katabi*
    
4. **A Closer Look at Deep Policy Gradients** ICLR 2020. [paper](https://openreview.net/pdf?id=ryxdEkHtPS)

    *Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry*

5. **Implementation Matters in Deep RL: A Case Study on PPO and TRPO** ICLR 2020. [paper](https://openreview.net/pdf?id=r1etN1rtPB)

    *Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry*
    
6. **A Generalized Training Approach for Multiagent Learning** ICLR 2020. [paper](https://openreview.net/pdf?id=Bkl5kxrKDr)

    *Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Perolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Remi Munos*

7. **Meta-Q-Learning** ICLR 2020. [paper](https://openreview.net/pdf?id=SJeD3CEFPH)

    *Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola*
    
8. **SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference** ICLR 2020. [paper](https://arxiv.org/pdf/1910.06591.pdf)

    *Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski*
