Designing Neural Net Architectures with Reinforcement Learning

Neural Architecture Search with Reinforcement Learning

Training Neural Nets with Simple Genetic Algorithms

Deep Neuroevolution - Genetic Algorithms to Train Deep Nets for RL

Learning Hierarchies to Solve a Range of RL Tasks

Meta Learning Shared Hierarchies by Frans et al.

Failure is Simply a Success at Something Else

Hindsight Experience Replay

Human Pose Imitation with Self-Supervised Learning

Time-Contrastive Networks. Self-Supervised Learning from Multi-View Observation

Model Agnostic Meta Learning

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Modular Policies for Multi-task Learning

Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer

Using Ensembles of Environtments to Learn Under Simulation Error

EPOpt - Robust Neural Net Policies Using Ensembles by Rajeswaran et al.

Benchmarking Recent Progress in Deep RL for Continuous Control

Benchmarking Deep Reinforcement Learning for Continuous Control