Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Riccardo Poli'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 Riccardo Poli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riccardo Poli more than expected).
This network shows the impact of papers produced by Riccardo Poli. 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 Riccardo Poli. The network helps show where Riccardo Poli may publish in the future.
Co-authorship network of co-authors of Riccardo Poli
This figure shows the co-authorship network connecting the top 25 collaborators of Riccardo Poli.
A scholar is included among the top collaborators of Riccardo Poli 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 Riccardo Poli. Riccardo Poli 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
1.
Poli, Riccardo. (2014). A model for characterising the collective dynamic behaviour of evolutionary algorithms. 147. 459–61.
Dorigo, Marco, Luca Maria Gambardella, Mauro Birattari, et al.. (2006). Ant Colony Optimization and Swarm Intelligence: 5th International Workshop, ANTS 2006, Brussels, Belgium, September 4-7, 2006, Proceedings (Lecture Notes in Computer Science). Springer eBooks.9 indexed citations
4.
Poli, Riccardo, et al.. (2005). On Turing complete T7 and MISC F-4 program fitness landscapes. UCL Discovery (University College London).1 indexed citations
Poli, Riccardo, Christopher R. Stephens, Alden H. Wright, & Jonathan E. Rowe. (2002). On the search biases of homologous crossover in linear genetic programming and variable-length genetic algorithms. Genetic and Evolutionary Computation Conference. 868–876.9 indexed citations
7.
Wright, Alden H., Jonathan E. Rowe, Riccardo Poli, & Christopher R. Stephens. (2002). A fixed point analysis of a gene pool GA with mutation. Genetic and Evolutionary Computation Conference. 642–649.10 indexed citations
8.
McPhee, Nicholas Freitag & Riccardo Poli. (2002). Using Schema Theory To Explore Interactions Of Multiple Operators. Genetic and Evolutionary Computation Conference. 853–860.13 indexed citations
9.
Poli, Riccardo, Jonathan E. Rowe, & Nicholas Freitag McPhee. (2001). Markov chain models for GP and variable-length GAs with homologous crossover. Genetic and Evolutionary Computation Conference. 112–119.15 indexed citations
Poli, Riccardo, et al.. (1999). Smooth Uniform Crossover with Smooth Point Mutation in Genetic Programming: A Preliminary Study. UCL Discovery (University College London). 39–48.22 indexed citations
12.
Poli, Riccardo, et al.. (1999). Solving Even-12, -13, -15, -17, -20 and -22 Boolean Parity Problems using Sub-machine Code GP with Smooth Uniform Crossover, Smooth Point Mutation and Demes. UCL Discovery (University College London).3 indexed citations
13.
Langdon, William B., et al.. (1999). Late-breaking papers of EuroGP-99. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–33.5 indexed citations
14.
Poli, Riccardo, et al.. (1999). Evolutionary image analysis, signal processing and telecommunications : first European workshops, EvoIASP '99 and EuroEcTel '99, Göteborg, Sweden, May 26-27, 1999 : proceedings. Springer eBooks.1 indexed citations
15.
Poli, Riccardo, et al.. (1999). Evolutionary discovery of learning rules for feedforward neural networks with step activation function. Genetic and Evolutionary Computation Conference. 1178–1183.1 indexed citations
Poli, Riccardo, et al.. (1998). Better Trained Ants for Genetic Programming. UCL Discovery (University College London).5 indexed citations
18.
Poli, Riccardo, et al.. (1997). A New Schema Theory for Genetic Programming with One-Point Crossover and Point Mutation. UCL Discovery (University College London).36 indexed citations
19.
Poli, Riccardo, et al.. (1997). Price’s Theorem and the MAX Problem. UCL Discovery (University College London).1 indexed citations
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.