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AI-based Problem Solving and Planning

AI-based Problem Solving and Planning is a research topic within Artificial Intelligence. Science Explorer counts 22k research works in it since 1955. 19.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on artificial intelligence planning and reasoning, covering topics such as planning systems, heuristic search, case-based reasoning, temporal planning, knowledge-based systems, robot control, model-based programming, probabilistic plan recognition, cognitive architecture, and autonomous systems.

  • Planning Systems
  • Heuristic Search
  • Case-Based Reasoning
  • Temporal Planning
  • Knowledge-Based Systems
  • Robot Control
  • Model-Based Programming
  • Probabilistic Plan Recognition
  • Cognitive Architecture
  • Autonomous Systems
Research works
22k
fractional, since 1955
In the world top 10%
4.3k
per year above
Top-10% rate
19.7%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-19%
the tick is no change

Which countries lead AI-based Problem Solving and Planning research?

By volume, the United States and China publish the most (488 and 337 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 488 works
  2. 2 China 337 works
  3. 3 Germany 176 works
  4. 4 United Kingdom 114 works
  5. 5 India 110 works
  6. 6 Italy 102 works
  7. 7 France 96 works
  8. 8 Spain 62 works
  9. 9 Canada 48 works
  10. 10 Japan 45 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.

United States: 30.9%China: 21.3%Germany: 11.2%United Kingdom: 7.2%6 others listed: 29.4%31%largest
United States488 · 30.9%China337 · 21.3%Germany176 · 11.2%United Kingdom114 · 7.2%6 others listed463 · 29.4%

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

Which institutions lead AI-based Problem Solving and Planning research?

By volume in 2022–2025, Carnegie Mellon University publishes the most AI-based Problem Solving and Planning research, followed by Centre National de la Recherche Scientifique and University of Brescia.

Who are the leading researchers in AI-based Problem Solving and Planning?

The most-cited researchers publishing on AI-based Problem Solving and Planning include Sebastian Thrun, Wolfram Burgard and Bùi Quang Minh.

  1. 1 Sebastian Thrun United States 10k citations
  2. 2 Wolfram Burgard Germany 6.3k citations
  3. 3 Bùi Quang Minh Australia 4.7k citations
  4. 4 John Seely Brown United States 4.6k citations

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

Where is AI-based Problem Solving and Planning research done?

The largest centres of AI-based Problem Solving and Planning research in 2022–2025 are Beijing (China), Shanghai (China), Paris (France) and London (United Kingdom).

Largest cities, 2022–2025

  1. 1 Beijing China 86 works
  2. 2 Shanghai China 27 works
  3. 3 Paris France 26 works
  4. 4 London United Kingdom 25 works
  5. 5 Guangzhou China 21 works
  6. 6 Pittsburgh United States 20 works
  7. 7 Xi'an China 19 works
  8. 8 Toulouse France 19 works
  9. 9 Munich Germany 19 works
  10. 10 Moscow Russia 19 works
See AI-based Problem Solving and Planning on the map

Where is the best place to study AI-based Problem Solving and Planning?

Among universities, judged by research, Carnegie Mellon University, University of Brescia and Georgia Institute of Technology 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%10%20%mean 10.69%fractional works in this node (log) →share in the world top 10% →Carnegie Mellon University: 16, 21.2%University of Brescia: 12, 7.3%Georgia Institute of Technology: 11, 15.8%Arizona State University: 10, 11.5%Czech Technical University in Prague: 9, 1.9%Massachusetts Institute of Technology: 10, 10.8%Linköping University: 9, 7.0%Australian National University: 10, 3.4%Beijing Institute of Technology: 9, 15.0%University of Southern California: 8, 13.0%Carnegie Mellon Univ…Georgia Institute of…Arizona State Univer…University of Brescia
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 Carnegie Mellon UniversityUnited States 86.721.2%19.0×16 +50.9%
2 University of BresciaItaly 55.57.3%33.9×12 +6.3%
3 Georgia Institute of TechnologyUnited States 55.415.8%8.1×11 +13.4%
4 Arizona State UniversityUnited States 50.411.5%7.2×10 +46.7%
5 Czech Technical University in PragueCzechia 47.41.9%17.2×9 +69.9%
6 Massachusetts Institute of TechnologyUnited States 46.510.8%7.9×10 -11.6%
7 Linköping UniversitySweden 44.57.0%14.9×9 -14.4%
8 Australian National UniversityAustralia 38.73.4%9.3×10 -24.8%
9 Beijing Institute of TechnologyChina 36.215.0%3.6×9 +25.9%
10 University of Southern CaliforniaUnited States 32.413.0%5.4×8 -10.2%

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 AI-based Problem Solving and Planning research growing?

Output in 2018–2022 was 19% lower than in 2013–2017, peaking in 2002.

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.