Rick Riolo

6.5k citations
99 papers · 5.1k · h-index 34

Impact in

Papers in

Rick Riolo

97 papers receiving 4.7k citations

Peers

Rick Riolo
Comparison fields: 5 of 188
  • Management Science and Operations Research 619
  • Artificial Intelligence 1.4k
  • Global and Planetary Change 805
  • Transportation 250
  • Safety Research 278
Replace Mathieu Jacomy with:
Mathieu Jacomy France
Frank Schweitzer Switzerland
Sébastien Heymann France
Steven F. Railsback United States
Katy Börner United States
David R. Hunter United States
Eric W. Bonabeau France
Alessandro Flammini United States
Charles M. Macal United States
Tamás Nepusz United Kingdom
Rick Riolo relative to Mathieu Jacomy France Mathieu Jacomy's profile →
Citations per field
00.5×2×3×3.7×
Mathieu Jacomy · 1×
Citations per year

Countries citing papers authored by Rick Riolo

Since Specialization
Citations

This map shows the geographic impact of Rick Riolo'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 Rick Riolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rick Riolo more than expected).

Fields of papers citing papers by Rick Riolo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rick Riolo. 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 Rick Riolo. The network helps show where Rick Riolo may publish in the future.

Co-authors

The 25 scholars most cited alongside Rick Riolo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rick Riolo Line = papers co-authored together Rick Riolo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001555
2 1998486
3 2005318
4 2005261
5 1999258
6 1999243
7 2006185
8 1972166
9
Genetic Programming 1997: Proceedings of the Second Annual Conference
1997149
10 1972132
11 2011129
12 2007115
13 2004109
14 200198
15 201497
16 200091
17 199179
18 201270
19 200760
20 200258

About Rick Riolo

Rick Riolo is a scholar working on Artificial Intelligence, Global and Planetary Change, Sociology and Political Science, Statistical and Nonlinear Physics and Economics and Econometrics, having authored 99 papers that have together received 5.1k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (39 papers), Metaheuristic Optimization Algorithms Research (25 papers), Evolutionary Game Theory and Cooperation (17 papers), Land Use and Ecosystem Services (11 papers), Reinforcement Learning in Robotics (9 papers), Opinion Dynamics and Social Influence (8 papers), Evolution and Genetic Dynamics (8 papers) and Complex Systems and Time Series Analysis (5 papers). The work is most often cited by research in Management Science and Operations Research (619 citations), Artificial Intelligence (1.4k citations), Global and Planetary Change (805 citations), Transportation (250 citations) and Safety Research (278 citations). Rick Riolo has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Robert S. Savit, Michael D. Cohen, Robert Axelrod, Daniel G. Brown, William M. Rand, H. Van Dyke Parunak, Bill Worzel, Vincent Hascall, Radu Manuca and Derek T. Robinson. Their work appears in journals such as Ecological Modelling, Nature, Machine Learning, Physica A Statistical Mechanics and its Applications and Environmental Science & Policy.

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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