Countries where authors publish in Genetic Programming and Evolvable Machines
Since Specialization
Citations
This map shows the geographic impact of research published in Genetic Programming and Evolvable Machines. 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 papers published in Genetic Programming and Evolvable Machines with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Genetic Programming and Evolvable Machines more than expected).
Fields of papers published in Genetic Programming and Evolvable Machines
This network shows the impact of papers published in Genetic Programming and Evolvable Machines. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Genetic Programming and Evolvable Machines.
About Genetic Programming and Evolvable Machines
The 527 papers published in Genetic Programming and Evolvable Machines in the last decades have received a total of 11.5k indexed citations . Papers published in Genetic Programming and Evolvable Machines usually cover Artificial Intelligence (391 papers), Computational Theory and Mathematics (72 papers), Molecular Biology (133 papers), Genetics (48 papers) and Computer Vision and Pattern Recognition (30 papers) specifically the topics of Evolutionary Algorithms and Applications (337 papers), Metaheuristic Optimization Algorithms Research (242 papers), Advanced Multi-Objective Optimization Algorithms (53 papers), Viral Infectious Diseases and Gene Expression in Insects (50 papers), Reinforcement Learning in Robotics (49 papers), Evolution and Genetic Dynamics (44 papers), Gene Regulatory Network Analysis (33 papers) and Neural Networks and Applications (24 papers). The most active scholars publishing in Genetic Programming and Evolvable Machines are Jeff Heaton, Kenneth O. Stanley, Carlos A. Coello Coello, Colin R. Reeves, William B. Langdon, John R. Koza, Michael O’Neill, Leonardo Vanneschi, Krzysztof Krawiec and Wolfgang Banzhaf.
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.