120 citations · 128 across the 5 of their papers we have counts for
3 papers · 1 filter
Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks
Adrian Ly, Richard Dazeley, Peter Vamplew +2
Deep Q-Networks algorithm (DQN) was the first reinforcement learning algorithm using deep neural network to successfully surpass human level performance in a number of Atari learni…
Discrete-to-Deep Supervised Policy Learning
Budi Kurniawan, Peter Vamplew, Michael Papasimeon +2
Neural networks are effective function approximators, but hard to train in the reinforcement learning (RL) context mainly because samples are correlated. For years, scholars have g…
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions
Peter Vamplew, Cameron Foale, Richard Dazeley
We report a previously unidentified issue with model-free, value-based approaches to multiobjective reinforcement learning in the context of environments with stochastic state tran…