David H. Ackley

7.1k total citations · 2 hit papers
42 papers, 4.1k citations indexed

About

David H. Ackley is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, David H. Ackley has authored 42 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 12 papers in Computational Theory and Mathematics and 8 papers in Computer Networks and Communications. Recurrent topics in David H. Ackley's work include Evolutionary Algorithms and Applications (11 papers), Modular Robots and Swarm Intelligence (8 papers) and Cellular Automata and Applications (7 papers). David H. Ackley is often cited by papers focused on Evolutionary Algorithms and Applications (11 papers), Modular Robots and Swarm Intelligence (8 papers) and Cellular Automata and Applications (7 papers). David H. Ackley collaborates with scholars based in United States, Switzerland and France. David H. Ackley's co-authors include Geoffrey E. Hinton, Terrence J. Sejnowski, Stephanie Forrest, Anil Somayaji, Alan S. Perelson, Derek J. Smith, Elena Gabriela Barrantes, Darko Stefanović, Michael L. Littman and Darko Stefanović and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Communications of the ACM and Cognitive Science.

In The Last Decade

David H. Ackley

39 papers receiving 3.7k citations

Hit Papers

A Learning Algorithm for Boltzmann Machines* 1985 2026 1998 2012 1985 1985 500 1000 1.5k
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 Learning Algorithm for Boltzmann Machines*
    1985 2.0k citations David H. Ackley, Geoffrey E. Hinton et al. Cognitive Science profile →
  2. A learning algorithm for boltzmann machines
    1985 380 citations David H. Ackley, Geoffrey E. Hinton et al. Cognitive Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David H. Ackley United States 14 2.4k 662 550 549 500 42 4.1k
Manfred Opper Germany 32 3.3k 1.4× 513 0.8× 364 0.7× 489 0.9× 732 1.5× 155 5.3k
Chris Watkins United Kingdom 14 2.7k 1.1× 154 0.2× 663 1.2× 308 0.6× 605 1.2× 33 5.5k
Witold Kinsner Canada 24 1.2k 0.5× 377 0.6× 337 0.6× 129 0.2× 536 1.1× 295 2.4k
Anh Huy Phan Japan 23 845 0.4× 1.4k 2.2× 331 0.6× 514 0.9× 863 1.7× 100 5.4k
Vwani Roychowdhury United States 39 2.1k 0.9× 370 0.6× 1.1k 2.0× 215 0.4× 247 0.5× 186 5.6k
Jeff Bilmes United States 37 3.6k 1.5× 1.2k 1.8× 622 1.1× 307 0.6× 1.6k 3.1× 199 6.4k
Francesco Piazza Italy 36 1.4k 0.6× 1.1k 1.7× 399 0.7× 234 0.4× 538 1.1× 397 6.2k
Daniel Hsu United States 30 2.2k 0.9× 342 0.5× 275 0.5× 119 0.2× 703 1.4× 86 4.0k
Jonathan S. Yedidia United States 22 1.4k 0.6× 401 0.6× 1.4k 2.5× 142 0.3× 922 1.8× 53 3.8k
Charles Sutton United States 34 3.5k 1.5× 688 1.0× 751 1.4× 186 0.3× 1.5k 2.9× 97 6.8k

Countries citing papers authored by David H. Ackley

Since Specialization
Citations

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

Fields of papers citing papers by David H. Ackley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David H. Ackley. 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 David H. Ackley. The network helps show where David H. Ackley may publish in the future.

Co-authorship network of co-authors of David H. Ackley

This figure shows the co-authorship network connecting the top 25 collaborators of David H. Ackley. A scholar is included among the top collaborators of David H. Ackley 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 David H. Ackley. David H. Ackley 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.
Jessen, Bart, Benno Rattel, David H. Ackley, et al.. (2025). Considerations of non-human primate use in nonclinical toxicity study package for oncology therapeutics with well-characterized target in supports of 3Rs – an IQ DruSafe industry survey. Regulatory Toxicology and Pharmacology. 162. 105902–105902.
2.
Ackley, David H., Todd Bourcier, Andrew L. Goodwin, et al.. (2022). FDA and industry collaboration: Identifying opportunities to further reduce reliance on nonhuman primates for nonclinical safety evaluations. Regulatory Toxicology and Pharmacology. 138. 105327–105327. 22 indexed citations
3.
Ackley, David H. & Hans Berliner. (2018). The QBKG system : knowledge representation for producing and explaining judgments. Figshare.
4.
Ackley, David H. & Elena S. Ackley. (2015). Artificial life programming in the robust-first attractor. 554–561. 2 indexed citations
5.
Ackley, David H. & Elena S. Ackley. (2015). Artificial life programming in the robust-first attractor. 13. 554–561. 4 indexed citations
6.
Ackley, David H., et al.. (2014). Indefinitely Scalable Computing = Artificial Life Engineering. 606–613. 8 indexed citations
7.
McDonald, David W., et al.. (2014). Antisocial computing. interactions. 21(6). 72–75. 3 indexed citations
8.
Ackley, David H. & Daniel C. Cannon. (2011). Pursue robust indefinite scalability. 8–8. 11 indexed citations
9.
Barrantes, Elena Gabriela, David H. Ackley, Stephanie Forrest, & Darko Stefanović. (2005). Randomized instruction set emulation. ACM Transactions on Information and System Security. 8(1). 3–40. 91 indexed citations
10.
Forrest, Stephanie, Anil Somayaji, & David H. Ackley. (2002). Building diverse computer systems. 67–72. 294 indexed citations
11.
Ackley, David H., et al.. (2002). Code factoring and the evolution of evolvability. Genetic and Evolutionary Computation Conference. 1383–1390. 24 indexed citations
12.
Ackley, David H. & Jonathan I. Helfman. (1999). Image representations for access and similarity-based organization of web information. BMC Plant Biology. 17(1). 260–260. 3 indexed citations
13.
Belew, Richard K., Melanie Mitchell, & David H. Ackley. (1996). Computation and the natural sciences. Addison-Wesley Longman Publishing Co., Inc. eBooks. 431–440. 6 indexed citations
14.
Littman, Michael L. & David H. Ackley. (1991). Adaptation in Constant Utility Non-Stationary Environments.. 136–142. 14 indexed citations
15.
Ackley, David H. & Michael L. Littman. (1989). Generalization and Scaling in Reinforcement Learning. Neural Information Processing Systems. 2. 550–557. 31 indexed citations
16.
Ackley, David H.. (1988). Associative Learning via Inhibitory Search. Neural Information Processing Systems. 1. 20–28. 6 indexed citations
17.
Ackley, David H.. (1987). Stochastic iterated genetic hillclimbing. 25 indexed citations
18.
Ackley, David H.. (1985). A Connectionist Algorithm for Genetic Search. international conference on Genetic algorithms. 121–135. 8 indexed citations
19.
Ackley, David H., Geoffrey E. Hinton, & Terrence J. Sejnowski. (1985). A learning algorithm for boltzmann machines. Cognitive Science. 9(1). 147–169. 380 indexed citations breakdown →
20.
Berliner, Hans & David H. Ackley. (1982). The QBKG system: generating explanations from a non-discrete knowledge representation. National Conference on Artificial Intelligence. 213–216. 9 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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