Andrew R. Gilpin

1.9k total citations
45 papers, 1.0k citations indexed

About

Andrew R. Gilpin is a scholar working on Management Science and Operations Research, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Andrew R. Gilpin has authored 45 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Management Science and Operations Research, 16 papers in Artificial Intelligence and 10 papers in Economics and Econometrics. Recurrent topics in Andrew R. Gilpin's work include Artificial Intelligence in Games (12 papers), Game Theory and Applications (9 papers) and Auction Theory and Applications (8 papers). Andrew R. Gilpin is often cited by papers focused on Artificial Intelligence in Games (12 papers), Game Theory and Applications (9 papers) and Auction Theory and Applications (8 papers). Andrew R. Gilpin collaborates with scholars based in United States, France and Denmark. Andrew R. Gilpin's co-authors include Tüomas Sandholm, David Levine, Subhash Suri, Javier Peña, Thomas Sandholm, Troels Bjerre Sørensen, Vincent Conitzer, Jane L. Wong, Stanley C. Ratner and Francisco X. Barrios and has published in prestigious journals such as Management Science, Journal of the ACM and Mathematical Programming.

In The Last Decade

Andrew R. Gilpin

43 papers receiving 959 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew R. Gilpin United States 14 579 343 227 212 202 45 1.0k
Magnus Boman Sweden 19 167 0.3× 334 1.0× 22 0.1× 54 0.3× 126 0.6× 86 1.2k
Piotr J. Gmytrasiewicz United States 18 301 0.5× 749 2.2× 16 0.1× 55 0.3× 167 0.8× 67 1.1k
José J. Padilla United States 16 327 0.6× 189 0.6× 16 0.1× 20 0.1× 100 0.5× 80 902
Neal Lathia United Kingdom 23 153 0.3× 282 0.8× 97 0.4× 16 0.1× 218 1.1× 40 2.4k
Michael Johanson Canada 14 300 0.5× 915 2.7× 9 0.0× 328 1.5× 58 0.3× 19 1.2k
Juan D. Velásquez Chile 20 70 0.1× 654 1.9× 57 0.3× 39 0.2× 94 0.5× 71 1.3k
Moninder Singh United States 17 94 0.2× 560 1.6× 36 0.2× 20 0.1× 92 0.5× 53 958
Ross Gore United States 18 166 0.3× 173 0.5× 13 0.1× 23 0.1× 49 0.2× 71 877
Jun Hong United Kingdom 14 101 0.2× 408 1.2× 16 0.1× 29 0.1× 109 0.5× 65 978
Derwin Suhartono Indonesia 19 58 0.1× 706 2.1× 35 0.2× 26 0.1× 36 0.2× 170 1.4k

Countries citing papers authored by Andrew R. Gilpin

Since Specialization
Citations

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

Fields of papers citing papers by Andrew R. Gilpin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew R. Gilpin. 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 Andrew R. Gilpin. The network helps show where Andrew R. Gilpin may publish in the future.

Co-authorship network of co-authors of Andrew R. Gilpin

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew R. Gilpin. A scholar is included among the top collaborators of Andrew R. Gilpin 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 Andrew R. Gilpin. Andrew R. Gilpin 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.
Gilpin, Andrew R., Tüomas Sandholm, & Troels Bjerre Sørensen. (2018). Potential-aware Automated Abstraction of Sequential Games, and Holistic Equilibrium Analysis of Texas Hold’em Poker. Open MIND. 50–57. 6 indexed citations
2.
Sandholm, Thomas, Andrew R. Gilpin, & Vincent Conitzer. (2018). Mixed-Integer Programming Methods for Finding Nash Equilibria. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 495–501. 14 indexed citations
3.
Gilpin, Andrew R. & Tüomas Sandholm. (2018). Optimal Rhode Island Hold’em Poker. Figshare. 1684–1685. 1 indexed citations
4.
Gilpin, Andrew R. & Tüomas Sandholm. (2018). A Competitive Texas Hold’em Poker Player via Automated Abstraction and Real-time Equilibrium Computation. Open MIND. 1007–1013. 11 indexed citations
5.
Sandholm, Tüomas & Andrew R. Gilpin. (2009). Algorithms for abstracting and solving imperfect information games. 11 indexed citations
6.
Gilpin, Andrew R. & Tüomas Sandholm. (2008). Solving two-person zero-sum repeated games of incomplete information. Adaptive Agents and Multi-Agents Systems. 903–910. 13 indexed citations
7.
Gilpin, Andrew R., Javier Peña, & Thomas Sandholm. (2008). First-order algorithm with O(ln(1/ε )) convergence for ε -equilibrium in two-person zero-sum games. National Conference on Artificial Intelligence. 75–82. 16 indexed citations
8.
Gilpin, Andrew R. & Thomas Sandholm. (2008). Expectation-based versus potential-aware automated abstraction in imperfect information games: an experimental comparison using poker. National Conference on Artificial Intelligence. 1454–1457. 9 indexed citations
9.
Gilpin, Andrew R., Tüomas Sandholm, & Troels Bjerre Sørensen. (2008). A heads-up no-limit Texas Hold'em poker player: discretized betting models and automatically generated equilibrium-finding programs. Adaptive Agents and Multi-Agents Systems. 911–918. 31 indexed citations
10.
Gilpin, Andrew R., et al.. (2007). A GRADIENT-BASED APPROACH FOR COMPUTING NASH EQUILIBRIA OF LARGE SEQUENTIAL GAMES. 6 indexed citations
11.
Gilpin, Andrew R. & Tüomas Sandholm. (2006). A Texas Hold'em poker player based on automated abstraction and real-time equilibrium computation. Figshare. 1453–1454. 12 indexed citations
12.
Sandholm, Tüomas, Subhash Suri, Andrew R. Gilpin, & David Levine. (2002). Winner determination in combinatorial auction generalizations. 69–76. 140 indexed citations
13.
Sandholm, Tüomas, Subhash Suri, Andrew R. Gilpin, & David Levine. (2002). Winner determination in combinatorial auction generalizations. 10 indexed citations
14.
Sandholm, Tüomas, Subhash Suri, Andrew R. Gilpin, & David Levine. (2001). CABOB: a fast optimal algorithm for combinatorial auctions. International Joint Conference on Artificial Intelligence. 1102–1108. 133 indexed citations
15.
Osman, Augustine, Andrew R. Gilpin, William F. Panak, et al.. (2000). The Multi‐Attitude Suicide Tendency Scale: Further Validation with Adolescent Psychiatric Inpatients. Suicide and Life-Threatening Behavior. 30(4). 377–385. 17 indexed citations
16.
Wong, Jane L. & Andrew R. Gilpin. (1993). Verbal vs. visual categories on the Wechsler memory scale - revised: How meaningful a distinction?. Journal of Clinical Psychology. 49(6). 847–854. 6 indexed citations
17.
Wong, Jane L. & Andrew R. Gilpin. (1991). Effects of Speed Vs Accuracy Instructions and Field Dependence on College Students' Digit-Symbol Matching Performance. Perceptual and Motor Skills. 73(1). 314–314. 3 indexed citations
18.
Gilpin, Andrew R., et al.. (1985). Parents’ child care experience: effects of sex and parity. Early Child Development and Care. 18(3-4). 161–173.
19.
Gilpin, Andrew R.. (1983). SCALO: A program to perform Guttman scaling analysis on the Apple II microcomputer. Behavior Research Methods. 15(5). 549–549. 1 indexed citations
20.
Gilpin, Andrew R.. (1979). Instructional Variations and Adults' Conceptual Tempo Performance. The Journal of General Psychology. 100(1). 53–61. 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.

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