Oliver Mihatsch

Reinforcement Learning · 1998

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 6 citations into it

Whom Oliver Mihatsch trusts overall

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

1. Richard S. Sutton
2. Dimitri P. Bertsekas
3. Geoffrey J. Gordon
4. John N. Tsitsiklis
5. Michael L. Littman
6. Ben J. A. Kröse
7. Martin L. Puterman
8. Andrew Barto

Who trusts Oliver Mihatsch overall

1. Trung Kien Vu
2. Medhi Bennis
3. Victoria Krakovna
4. Stefan Depeweg
5. Christopher G. Atkeson
6. Jun Morimoto

Papers from Oliver Mihatsch's perspective

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

1. Stable Function Approximation in Dynamic Programming
2. Learning to predict by the methods of temporal differences
3. Dynamic Programming and Optimal Control, Two Volume Set
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Linear Least-Squares algorithms for temporal difference learning
7. Gradient-based learning applied to document recognition
8. Residual Algorithms: Reinforcement Learning with Function Approximation
9. A Generalized Reinforcement-Learning Model: Convergence and Applications
10. Reinforcement Learning: An Introduction

Their papers

• Risk-Sensitive Reinforcement Learning (1998)