Tom Schaul

Publications by Year

Research Areas

Reinforcement Learning in Robotics, Evolutionary Algorithms and Applications, Artificial Intelligence in Games, Metaheuristic Optimization Algorithms Research, Neural Networks and Applications

Most-Cited Works

• → Grandmaster level in StarCraft II using multi-agent reinforcement learning(2019)3,358 cited
• → Prioritized Experience Replay(2015)2,034 cited
• → Dueling Network Architectures for Deep Reinforcement Learning(2015)1,813 cited
• → Rainbow: Combining Improvements in Deep Reinforcement Learning(2018)1,691 cited
• → Deep Q-learning From Demonstrations(2018)795 cited
• → StarCraft II: A New Challenge for Reinforcement Learning(2017)683 cited
• Unifying count-based exploration and intrinsic motivation(2016)
• Universal Value Function Approximators(2015)
• → Learning to learn by gradient descent by gradient descent(2016)344 cited