Saminda Abeyruwan

Reinforcement Learning · 2015–2025

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 11 citations into it

Whom Saminda Abeyruwan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Hamid Reza Maei
3. Thomas Degris
4. Matthew E. Taylor
5. Andrew Barto
6. Harm van Seijen
7. Patrick M. Pilarski
8. Csaba Szepesvari
9. Gregory Kuhlmann
10. Peter Stone

Papers from Saminda Abeyruwan's perspective

Ordered by how strongly the researchers Saminda Abeyruwan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. ImageNet classification with deep convolutional neural networks
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
8. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
9. Human-level control through deep reinforcement learning
10. Residual Algorithms: Reinforcement Learning with Function Approximation

Their papers

• Gemini Robotics: Bringing AI into the Physical World (2025) — 385 citations
• RLLib: C++ Library to Predict, Control, and Represent Learnable Knowledge Using On/Off Policy Reinforcement Learning (2015)