Martin Riedmiller

86 papers receiving 22.1k citations

Hit Papers

Human-level control through deep reinfo...200220262010201820152002201520145.0k10.0k15.0k

Peers

Martin Riedmiller
Comparison fields: 5 of 211
  • Artificial Intelligence 10.2k
  • Electrical and Electronic Engineering 4.4k
  • Computer Vision and Pattern Recognition 4.3k
  • Control and Systems Engineering 4.3k
  • Computer Networks and Communications 3.7k
Replace Daan Wierstra with:
Daan Wierstra Switzerland
Joel Veness Canada
Andrei A. Rusu United Kingdom
Georg Ostrovski United Kingdom
Timothy Lillicrap United States
Marc G. Bellemare United States
Volodymyr Mnih United States
Shane Legg Switzerland
Andreas Fidjeland United Kingdom
Ioannis Antonoglou United Kingdom
Martin Riedmiller relative to Daan Wierstra Switzerland Daan Wierstra's profile →
Citations per field
00.5×1.6×
Daan Wierstra · 1×
Citations per year

Countries citing papers authored by Martin Riedmiller

Since Specialization
Citations

This map shows the geographic impact of Martin Riedmiller's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Riedmiller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Riedmiller more than expected).

Fields of papers citing papers by Martin Riedmiller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Riedmiller. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Riedmiller. The network helps show where Martin Riedmiller may publish in the future.

Co-authorship network of co-authors of Martin Riedmiller

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Riedmiller. A scholar is included among the top collaborators of Martin Riedmiller based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Riedmiller. Martin Riedmiller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 5
3
A Constrained Multi-Objective Reinforcement Learning Framework
2
4
Data-efficient Hindsight Off-policy Option Learning
3
5
Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion
2
6
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning
17
7
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
3
8
Controlling biological neural networks with deep reinforcement learning.
1
9
Learning an Embedding Space for Transferable Robot Skills
66
10
Maximum a Posteriori Policy Optimisation
10
11
Learning by Playing - Solving Sparse Reward Tasks from Scratch
48
12
Human-level control through deep reinforcement learningbreakdown →
17153
13
Discriminative Unsupervised Feature Learning with Convolutional Neural Networksbreakdown →
289
14
Electricity demand forecasting using Gaussian processes
25
15
Deep learning of visual control policies.
13
16 4
17
Reinforcement Learning in a Nutshell
12
18
Reducing policy degradation in neuro-dynamic programming.
8
19
Learning a Partial Behavior for a Competitive Robotic Soccer Agent
8
20
A neural reinforcement learning approach to learn local dispatching policies in production scheduling
42

About Martin Riedmiller

Martin Riedmiller is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 90 papers that have together received 23.2k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (43 papers), Advanced Control Systems Optimization (18 papers) and Neural Networks and Applications (12 papers). The work is most often cited by research in Artificial Intelligence (10.2k citations), Computer Vision and Pattern Recognition (4.3k citations) and Control and Systems Engineering (4.3k citations). Martin Riedmiller has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Heinrich Braun, Volodymyr Mnih, Charles Beattie, Dharshan Kumaran, Georg Ostrovski, Marc G. Bellemare, Andreas Fidjeland, Koray Kavukcuoglu, Ioannis Antonoglou and Stig Petersen. Their work appears in journals such as Nature, IEEE Transactions on Pattern Analysis and Machine Intelligence and Frontiers in Psychology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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