Nolan Bard

1.4k total citations · 1 hit paper
17 papers, 654 citations indexed

About

Nolan Bard is a scholar working on Artificial Intelligence, Economics and Econometrics and Clinical Psychology. According to data from OpenAlex, Nolan Bard has authored 17 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Economics and Econometrics and 6 papers in Clinical Psychology. Recurrent topics in Nolan Bard's work include Artificial Intelligence in Games (15 papers), Sports Analytics and Performance (7 papers) and Gambling Behavior and Treatments (6 papers). Nolan Bard is often cited by papers focused on Artificial Intelligence in Games (15 papers), Sports Analytics and Performance (7 papers) and Gambling Behavior and Treatments (6 papers). Nolan Bard collaborates with scholars based in Canada, United States and United Kingdom. Nolan Bard's co-authors include Michael Bowling, Neil Burch, Michael Johanson, Kevin Waugh, Dustin Morrill, Trevor Davis, Matej Moravčík, Martin Schmid, Viliam Lisý and Marc Lanctot and has published in prestigious journals such as Science, Science Advances and Computers in Human Behavior.

In The Last Decade

Nolan Bard

17 papers receiving 610 citations

Hit Papers

align trajectories

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.

DeepStack: Expert-level artificial intelligence in heads-up no-limit poker

2017 409 citations Matej Moravčík, Martin Schmid et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nolan Bard Canada	9	443	126	93	92	84	17	654
Noam Brown United States	9	495 1.1×	109 0.9×	170 1.8×	105 1.1×	69 0.8×	19	692
Trevor Davis United States	5	293 0.7×	75 0.6×	59 0.6×	94 1.0×	41 0.5×	8	480
Viliam Lisý Czechia	11	415 0.9×	100 0.8×	113 1.2×	83 0.9×	46 0.5×	35	725
Dustin Morrill Canada	4	285 0.6×	71 0.6×	69 0.7×	58 0.6×	37 0.4×	7	437
Matej Moravčík Czechia	3	282 0.6×	72 0.6×	59 0.6×	62 0.7×	40 0.5×	7	424
Michael Johanson Canada	14	915 2.1×	328 2.6×	300 3.2×	207 2.3×	190 2.3×	19	1.2k
Hiroyuki Iida Japan	14	338 0.8×	143 1.1×	19 0.2×	249 2.7×	54 0.6×	129	602
Michael van Lent United States	12	512 1.2×	25 0.2×	37 0.4×	119 1.3×	7 0.1×	34	783
Ayu Purwarianti Indonesia	16	915 2.1×	21 0.2×	28 0.3×	83 0.9×	11 0.1×	178	1.2k
Peng Qian China	15	380 0.9×	51 0.4×	20 0.2×	53 0.6×	5 0.1×	45	907

Countries citing papers authored by Nolan Bard

Since Specialization

Citations

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

Fields of papers citing papers by Nolan Bard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nolan Bard

This figure shows the co-authorship network connecting the top 25 collaborators of Nolan Bard. A scholar is included among the top collaborators of Nolan Bard 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 Nolan Bard. Nolan Bard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Schmid, Martin, Matej Moravčík, Neil Burch, et al.. (2023). Student of Games: A unified learning algorithm for both perfect and imperfect information games. Science Advances. 9(46). eadg3256–eadg3256. 1 indexed citations

2.

Bard, Nolan, Edward Lockhart, Marc Lanctot, et al.. (2022). Approximate Exploitability: Learning a Best Response. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 3487–3493. 6 indexed citations

3.

Johanson, Michael, Nolan Bard, Neil Burch, & Michael Bowling. (2021). Finding Optimal Abstract Strategies in Extensive-Form Games. Proceedings of the AAAI Conference on Artificial Intelligence. 26(1). 1371–1379. 4 indexed citations

4.

Bard, Nolan, Jakob Foerster, Sarath Chandar, et al.. (2019). The Hanabi challenge: A new frontier for AI research. Artificial Intelligence. 280. 103216–103216. 100 indexed citations

5.

Moravčík, Matej, Martin Schmid, Neil Burch, et al.. (2017). DeepStack: Expert-level artificial intelligence in heads-up no-limit poker. Science. 356(6337). 508–513. 409 indexed citations breakdown →

6.

Bard, Nolan. (2016). Online Agent Modelling in Human-Scale Problems. University of Alberta Library. 2 indexed citations

7.

Bard, Nolan, et al.. (2015). Decision-theoretic Clustering of Strategies. Adaptive Agents and Multi-Agents Systems. 17–25. 5 indexed citations

8.

Bard, Nolan, Michael Johanson, & Michael Bowling. (2014). Asymmetric abstractions for adversarial settings. Adaptive Agents and Multi-Agents Systems. 501–508. 3 indexed citations

9.

Bard, Nolan, Michael Johanson, Neil Burch, & Michael Bowling. (2013). Online implicit agent modelling. Adaptive Agents and Multi-Agents Systems. 255–262. 24 indexed citations

10.

Bard, Nolan, et al.. (2013). The Annual Computer Poker Competition. AI Magazine. 34(2). 112–114. 10 indexed citations

11.

Bard, Nolan, et al.. (2013). Do pokers players know how good they are? Accuracy of poker skill estimation in online and offline players. Computers in Human Behavior. 31. 419–424. 18 indexed citations

12.

Johanson, Michael, Nolan Bard, Marc Lanctot, Richard G. Gibson, & Michael Bowling. (2012). Efficient Nash equilibrium approximation through Monte Carlo counterfactual regret minimization. Adaptive Agents and Multi-Agents Systems. 837–846. 23 indexed citations

13.

Waugh, Kevin, Nolan Bard, & Michael Bowling. (2009). Strategy Grafting in Extensive Games. Neural Information Processing Systems. 22. 2026–2034. 12 indexed citations

14.

Bowling, Michael, Nolan Bard, Darse Billings, et al.. (2009). A demonstration of the Polaris poker system. Adaptive Agents and Multi-Agents Systems. 1391–1392. 4 indexed citations

15.

Bard, Nolan & Michael Bowling. (2007). Particle filtering for dynamic agent modelling in simplified poker. National Conference on Artificial Intelligence. 515–521. 14 indexed citations

16.

Zinkevich, Martin, et al.. (2006). Optimal unbiased estimators for evaluating agent performance. National Conference on Artificial Intelligence. 573–578. 14 indexed citations

17.

Lee, Mark, et al.. (2004). The Trellis Security Infrastructure: A Layered Approach to Overlay Metacomputers .. 109–117. 5 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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