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https://github.com/ajaysub110/paper-a-day

keeps the doctor away
https://github.com/ajaysub110/paper-a-day

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keeps the doctor away

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README

        

# Reading list

**Model-based RL**

Hafner, Danijar, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba. “Mastering Atari with Discrete World Models.” ArXiv:2010.02193 [Cs, Stat], October 5, 2020. http://arxiv.org/abs/2010.02193.

**Cognitive Science / Neuro-Symbolic**

Cranmer, Miles, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, and Shirley Ho. “Discovering Symbolic Models from Deep Learning with Inductive Biases,” n.d., 14.

Anonymous. “HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving,” 2020. https://openreview.net/forum?id=D51irFX8UOG.

Lake, Brenden M., Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman. “Building Machines That Learn and Think Like People.” ArXiv:1604.00289 [Cs, Stat], November 2, 2016. http://arxiv.org/abs/1604.00289.

**Neuroscience**

Richards, Blake A. “Moving beyond Reward Prediction Errors.” Nature Machine Intelligence 1, no. 5 (May 2019): 204–5. https://doi.org/10.1038/s42256-019-0053-0.

**Representation Learning**

Le-Khac, Phuc H., Graham Healy, and Alan F. Smeaton. “Contrastive Representation Learning: A Framework and Review.” IEEE Access 8 (2020): 193907–34. https://doi.org/10.1109/ACCESS.2020.3031549.

**Multi-Agent RL**

Xie, Annie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, and Dorsa Sadigh. “Learning Latent Representations to Influence Multi-Agent Interaction.” ArXiv:2011.06619 [Cs], November 12, 2020. http://arxiv.org/abs/2011.06619.