Friday, September 21st, 2018 at 11am – LIP meeting room M7 3rd floor
Jacobo Levy-Abitbol will be giving a presentation of the paper “Human-level control through deep reinforcement learning” published by Mnih et al. in Nature in 2015. From the abstract:
Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games.
Full details on the Journal Club’s repository.
Human-level control through deep reinforcement learning, Mnih et al. (2015)
