Philip Hingston

5.1k total citations · 2 hit papers
71 papers, 3.5k citations indexed

About

Philip Hingston is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Philip Hingston has authored 71 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 15 papers in Computational Theory and Mathematics and 12 papers in Computer Networks and Communications. Recurrent topics in Philip Hingston's work include Artificial Intelligence in Games (19 papers), Evolutionary Algorithms and Applications (18 papers) and Reinforcement Learning in Robotics (10 papers). Philip Hingston is often cited by papers focused on Artificial Intelligence in Games (19 papers), Evolutionary Algorithms and Applications (18 papers) and Reinforcement Learning in Robotics (10 papers). Philip Hingston collaborates with scholars based in Australia, United Kingdom and Singapore. Philip Hingston's co-authors include Luigi Barone, Lyndon While, Simon Huband, Martin Mašek, Ross Wilkinson, Graham Kendall, Erwin Adi, Zubair Baig, Lucas Bradstreet and Jiawei Li and has published in prestigious journals such as Australasian Journal of Paramedicine, IEEE Transactions on Evolutionary Computation and Applied Soft Computing.

In The Last Decade

Philip Hingston

70 papers receiving 3.4k citations

Hit Papers

A review of multiobjective test problems and a scalable t... 2006 2026 2012 2019 2006 2006 400 800 1.2k
What are hit papers?

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.

  1. A review of multiobjective test problems and a scalable test problem toolkit
    2006 1.5k citations Simon Huband, Philip Hingston et al. profile →
  2. A faster algorithm for calculating hypervolume
    2006 805 citations Lyndon While, Philip Hingston et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Philip Hingston Australia 21 2.3k 2.1k 498 307 222 71 3.5k
Liqun Gao China 26 1.0k 0.5× 789 0.4× 493 1.0× 268 0.9× 173 0.8× 184 2.8k
Mostafa Z. Ali Jordan 25 1.9k 0.8× 1.2k 0.6× 110 0.2× 299 1.0× 122 0.5× 93 2.9k
Matthew E. Taylor United States 32 2.6k 1.1× 398 0.2× 314 0.6× 829 2.7× 484 2.2× 160 3.8k
Michael Georgeff Australia 22 2.3k 1.0× 253 0.1× 246 0.5× 179 0.6× 472 2.1× 53 2.9k
Hideyuki Takagi Japan 23 1.5k 0.7× 403 0.2× 106 0.2× 396 1.3× 84 0.4× 131 3.1k
Alan Fern United States 30 2.1k 0.9× 183 0.1× 205 0.4× 268 0.9× 391 1.8× 172 2.9k
Pascal Poupart Canada 26 1.5k 0.7× 243 0.1× 280 0.6× 200 0.7× 382 1.7× 117 2.4k
Fernando Fernández Spain 19 1.0k 0.5× 182 0.1× 111 0.2× 503 1.6× 112 0.5× 86 1.8k
Pier Luca Lanzi Italy 35 2.5k 1.1× 179 0.1× 100 0.2× 212 0.7× 387 1.7× 176 3.8k
Charles L. Isbell United States 22 1.4k 0.6× 151 0.1× 107 0.2× 295 1.0× 142 0.6× 105 2.0k

Countries citing papers authored by Philip Hingston

Since Specialization
Citations

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

Fields of papers citing papers by Philip Hingston

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Hingston

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Hingston. A scholar is included among the top collaborators of Philip Hingston 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 Philip Hingston. Philip Hingston 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.
Mašek, Martin, et al.. (2016). Modeling perceived difficulty in game levels. Australasian Journal of Paramedicine. 1–8. 9 indexed citations
2.
Hingston, Philip, et al.. (2015). Evolving statistical rulesets for network intrusion detection. Applied Soft Computing. 33. 348–359. 48 indexed citations
3.
Hingston, Philip. (2012). Believable Bots: Can Computers Play Like People?. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 23 indexed citations
4.
Hingston, Philip, et al.. (2011). Analysis of key installation protection using computerized red teaming. Bone Reports. 17. 137–144. 2 indexed citations
5.
Low, Malcolm Yoke Hean, et al.. (2011). Studies on Pareto-based multi-objective competitive coevolutionary dynamics. 2383–2390. 1 indexed citations
6.
Hingston, Philip. (2010). A new design for a Turing Test for Bots. Australasian Journal of Paramedicine. 345–350. 47 indexed citations
7.
Hingston, Philip, et al.. (2009). Using a Virtual Body to Aid in Exergaming System Development. IEEE Computer Graphics and Applications. 29(2). 39–48. 10 indexed citations
8.
Hingston, Philip, et al.. (2009). Team 1: Applying Automated Red Teaming in a Maritime Scenario. 8 indexed citations
9.
Hingston, Philip, Luigi Barone, & Zbigniew Michalewicz. (2008). Design by Evolution: Advances in Evolutionary Design. UWA Profiles and Research Repository (University of Western Australia). 22 indexed citations
10.
Barone, Luigi, et al.. (2006). Fixture-scheduling for the Australian Football League using a Multi-Objective Evolutionary Algorithm. Australasian Journal of Paramedicine. 2740. 954–961. 3 indexed citations
11.
Barone, Luigi, Lyndon While, Simon Huband, & Philip Hingston. (2005). A Scalable Multi-objective Test Problem Toolkit. UWA Profiles and Research Repository (University of Western Australia). 3410. 280–295. 7 indexed citations
12.
While, Lyndon, Lucas Bradstreet, Luigi Barone, & Philip Hingston. (2005). Heuristics for Optimising the Calculation of Hypervolume for Multi-objective Optimisation Problems. Australasian Journal of Paramedicine. 3. 2225–2232. 44 indexed citations
13.
Huband, Simon, et al.. (2005). Designing Comminution Circuits with a Multi-Objective Evolutionary Algorithm. Australasian Journal of Paramedicine. 2. 1815–1822. 12 indexed citations
14.
Hingston, Philip & Graham Kendall. (2004). Learning versus evolution in iterated prisoner's dilemma. 364–372. 25 indexed citations
15.
Oliver, Ron, et al.. (2003). Exploring the reusability of Web-based learning resources. Australasian Journal of Paramedicine. 2003(1). 115–122. 3 indexed citations
16.
Barone, Luigi, Lyndon While, & Philip Hingston. (2002). Designing Crushers With A Multi-objective Evolutionary Algorithm. Genetic and Evolutionary Computation Conference. 995–1002. 14 indexed citations
17.
Hingston, Philip. (2001). A genetic algorithm for regular inference. Australasian Journal of Paramedicine. 1299–1306. 3 indexed citations
18.
Wilkinson, Ross & Philip Hingston. (1992). Incorporating the vector space model in a neural network used for document retrieval. Library Hi Tech. 10(1/2). 69–75. 7 indexed citations
19.
Wilkinson, Ross & Philip Hingston. (1991). Using the Cosine Measure in a Neural Network for Document.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 202–210. 11 indexed citations
20.
Wilkinson, Ross & Philip Hingston. (1991). Using the cosine measure in a neural network for document retrieval. 202–210. 87 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.

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