papers

papers copied to clipboard

2018-05

• Progress & Compress: A scalable framework for continual learning [arxiv] & [notes]
• Playing hard exploration games by watching YouTube [arxiv] & [notes]

2018-04

• DORA The Explorer: Directed Outreaching Reinforcement Action-Selection [arxiv] & [notes]
• Gotta Learn Fast: A New Benchmark for Generalization in RL [arxiv] & [notes]

2018-03

• An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling [arxiv] & [notes]
• Generative Multi-Agent Behavioral Cloning [arxiv] & [notes]
• World Models [arxiv] & [notes]
• Semi-parametric Topological Memory for Navigation [arxiv] & [notes]
• A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay [arxiv] & [notes]

2018-02

• Model-Ensemble Trust-Region Policy Optimization [arxiv] & [notes]

2018-01

• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor [arxiv] & [notes]

2017-08

• A Brief Survey of Deep Reinforcement Learning [arxiv] & [notes]
• Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control [arxiv] & [notes]

2017-07

• Distral: Robust Multitask Reinforcement Learning [arxiv] & [notes]

2017-03

• Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [arxiv] & [notes]

2017-02

• Cognitive Mapping and Planning for Visual Navigation [arxiv] & [notes]

2016-06

• Progressive Neural Networks [arxiv] & [notes]