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Topic · Artificial Intelligence

Reinforcement Learning in Robotics

Reinforcement Learning in Robotics is a research topic within Artificial Intelligence. Science Explorer counts 21k research works in it since 1956. 21.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers encompasses a wide range of advancements in reinforcement learning algorithms and their applications, including deep learning, neural networks, robotics, autonomous control, policy gradient methods, multi-agent systems, model-based learning, curiosity-driven exploration, and simulation to real-world transfer.

  • Reinforcement Learning
  • Deep Learning
  • Neural Networks
  • Robotics
  • Autonomous Control
  • Policy Gradient
  • Multi-Agent Systems
  • Model-Based Learning
  • Curiosity-Driven Exploration
  • Simulation to Real-world Transfer
Research works
21k
fractional, since 1956
In the world top 10%
4.3k
per year above
Top-10% rate
21.0%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+125%
the tick is no change

Which countries lead Reinforcement Learning in Robotics research?

By volume, China and the United States publish the most (2.3k and 1.3k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.3k works
  2. 2 United States 1.3k works
  3. 3 United Kingdom 316 works
  4. 4 Germany 303 works
  5. 5 Japan 266 works
  6. 6 India 262 works
  7. 7 Canada 190 works
  8. 8 South Korea 179 works
  9. 9 Italy 165 works
  10. 10 France 147 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 42.7%United States: 24.1%United Kingdom: 5.7%Germany: 5.5%6 others listed: 22.0%43%largest
China2,347 · 42.7%United States1,322 · 24.1%United Kingdom316 · 5.7%Germany303 · 5.5%6 others listed1,209 · 22.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Reinforcement Learning in Robotics research?

By volume in 2022–2025, Tsinghua University publishes the most Reinforcement Learning in Robotics research, followed by National University of Defense Technology and Shanghai Jiao Tong University.

By volume, 2022–2025

  1. 1 Tsinghua UniversityChina 95 works
  2. 2 National University of Defense TechnologyChina 77 works
  3. 3 Shanghai Jiao Tong UniversityChina 61 works
  4. 4 Northwestern Polytechnical UniversityChina 53 works
  5. 5 Beihang UniversityChina 52 works
  6. 6 Beijing Institute of TechnologyChina 50 works
  7. 7 Chinese Academy of SciencesChina 48 works
  8. 8 Carnegie Mellon UniversityUnited States 48 works
  9. 9 Harbin Institute of TechnologyChina 48 works
  10. 10 Georgia Institute of TechnologyUnited States 38 works

Who are the leading researchers in Reinforcement Learning in Robotics?

The most-cited researchers publishing on Reinforcement Learning in Robotics include Scott Reed, Li Fei-Fei and Yoshua Bengio.

  1. 1 Scott Reed United States 17k citations
  2. 2 Li Fei-Fei United States 17k citations
  3. 3 Yoshua Bengio Canada 17k citations
  4. 4 Jitendra Malik United States 12k citations
  5. 5 Ion Stoica United States 9.6k citations
  6. 6 Oriol Vinyals United States 7.4k citations
  7. 7 Soumith Chintala Israel 6.9k citations
  8. 8 Trevor Darrell United States 6.7k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Reinforcement Learning in Robotics research done?

The largest centres of Reinforcement Learning in Robotics research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Xi'an (China).

Largest cities, 2022–2025

  1. 1 Beijing China 586 works
  2. 2 Shanghai China 204 works
  3. 3 Nanjing China 174 works
  4. 4 Xi'an China 131 works
  5. 5 Changsha China 119 works
  6. 6 Tokyo Japan 100 works
  7. 7 Shenzhen China 98 works
  8. 8 Singapore Singapore 95 works
  9. 9 Guangzhou China 92 works
  10. 10 London United Kingdom 91 works
See Reinforcement Learning in Robotics on the map

Where is the best place to study Reinforcement Learning in Robotics?

Among universities, judged by research, Tsinghua University, National University of Defense Technology and Nanyang Technological University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 26.35%fractional works in this node (log) →share in the world top 10% →Tsinghua University: 95, 23.1%National University of Defense Technology: 77, 18.3%Nanyang Technological University: 37, 34.5%University of California, Berkeley: 31, 34.5%Beihang University: 52, 24.0%Carnegie Mellon University: 48, 18.2%Northeastern University: 34, 30.0%University of Technology Sydney: 14, 44.6%Beijing Institute of Technology: 50, 16.6%Shanghai Jiao Tong University: 61, 19.7%Nanyang Technologica…University of Califo…Tsinghua UniversityNational University …
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Tsinghua UniversityChina 66.723.1%7.2×95 +165.7%
2 National University of Defense TechnologyChina 65.918.3%14.7×77 +147.8%
3 Nanyang Technological UniversitySingapore 64.334.5%6.9×37 +35.6%
4 University of California, BerkeleyUnited States 63.934.5%5.4×31 +271.5%
5 Beihang UniversityChina 63.324.0%7.0×52 +264.2%
6 Carnegie Mellon UniversityUnited States 62.518.2%17.5×48 +109.0%
7 Northeastern UniversityChina 60.530.0%5.7×34 +391.2%
8 University of Technology SydneyAustralia 58.544.6%4.6×14 +69.7%
9 Beijing Institute of TechnologyChina 55.316.6%6.2×50 +252.2%
10 Shanghai Jiao Tong UniversityChina 54.419.7%4.2×61 +239.8%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Reinforcement Learning in Robotics research growing?

Output in 2018–2022 was 125% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Reinforcement Learning in Robotics.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.