Volkmar Sterzing

Reinforcement Learning · 2017

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 21 citations into it
• Artificial Intelligence — 11 citations into it; #35,065 of 35,345 by trust here, #25,040 by citations
• Control and Systems Engineering — 5 citations into it

Whom Volkmar Sterzing trusts

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

1. Martin A. Riedmiller (in Reinforcement Learning)
2. Ben J. A. Kröse (in Reinforcement Learning)
3. Richard S. Sutton (in Reinforcement Learning)

Who trusts Volkmar Sterzing

1. Steffen Udluft (in Artificial Intelligence)

Papers from Volkmar Sterzing's perspective

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

1. Reinforcement Learning: An Introduction
2. Human-level control through deep reinforcement learning
3. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
4. The Arcade Learning Environment: An Evaluation Platform for General Agents
5. Mastering the game of Go with deep neural networks and tree search
6. MuJoCo: A physics engine for model-based control
7. Learning to Drive a Bicycle Using Reinforcement Learning and Shaping
8. Learning from delayed rewards
9. Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method
10. Batch Reinforcement Learning

Their papers

• A benchmark environment motivated by industrial control problems (2017) — 68 citations
• Batch reinforcement learning on the industrial benchmark: First experiences (2017) — 12 citations