57 citations · 98 across the 7 of their papers we have counts for
3 papers · 1 filter
Implementing the Deep Q-Network
Melrose Roderick, James MacGlashan, Stefanie Tellex
The Deep Q-Network proposed by Mnih et al. [2015] has become a benchmark and building point for much deep reinforcement learning research. However, replicating results for complex…
Deep Abstract Q-Networks
Melrose Roderick, Christopher Grimm, Stefanie Tellex
We examine the problem of learning and planning on high-dimensional domains with long horizons and sparse rewards. Recent approaches have shown great successes in many Atari 2600 d…
Mean Actor Critic
Cameron Allen, Kavosh Asadi, Melrose Roderick +3
We propose a new algorithm, Mean Actor-Critic (MAC), for discrete-action continuous-state reinforcement learning. MAC is a policy gradient algorithm that uses the agent's explicit…