Sim-to-Real Robot Learning from Pixels with Progressive Nets. - Andrei A. Rusu; Matej Vecerík; Thomas Rothörl; Nicolas Heess; Razvan Pascanu; Raia Hadsell (CoRL, 2017)

Learning from Demonstrations for Real World Reinforcement Learning. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Andrew Sendonaris; Gabriel Dulac-Arnold; Ian Osband; John P. Agapiou; Joel Z. Leibo; Audrunas Gruslys (CoRR, 2017)

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation. - Ivaylo Popov; Nicolas Heess; Timothy P. Lillicrap; Roland Hafner; Gabriel Barth-Maron; Matej Vecerík; Thomas Lampe; Yuval Tassa; Tom Erez; Martin A. Riedmiller (CoRR, 2017)

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. - Matej Vecerík; Todd Hester; Jonathan Scholz; Fumin Wang; Olivier Pietquin; Bilal Piot; Nicolas Heess; Thomas Rothörl; Thomas Lampe; Martin A. Riedmiller (CoRR, 2017)

Deep Q-learning From Demonstrations. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Dan Horgan; John Quan; Andrew Sendonaris; Ian Osband; Gabriel Dulac-Arnold; John P. Agapiou; et al. (AAAI, 2018)

Safe Exploration in Continuous Action Spaces. - Gal Dalal; Krishnamurthy Dvijotham; Matej Vecerík; Todd Hester; Cosmin Paduraru; Yuval Tassa (CoRR, 2018)