G. Tesauro

3.2k total citations · 2 hit papers
22 papers, 2.2k citations indexed

About

G. Tesauro is a scholar working on Artificial Intelligence, Computer Networks and Communications and Condensed Matter Physics. According to data from OpenAlex, G. Tesauro has authored 22 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 3 papers in Condensed Matter Physics. Recurrent topics in G. Tesauro's work include Neural Networks and Applications (6 papers), Artificial Intelligence in Games (4 papers) and Neural dynamics and brain function (3 papers). G. Tesauro is often cited by papers focused on Neural Networks and Applications (6 papers), Artificial Intelligence in Games (4 papers) and Neural dynamics and brain function (3 papers). G. Tesauro collaborates with scholars based in United States and United Kingdom. G. Tesauro's co-authors include David S. Touretzky, Todd K. Leen, R. Das, Jeffrey O. Kephart, William E. Walsh, Mohamed N. Bennani, Nicholas K. Jong, Terrence J. Sejnowski, Gregory B. Sorkin and M. C. Cross and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Optics Letters and Artificial Intelligence.

In The Last Decade

G. Tesauro

22 papers receiving 2.0k 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.

Advances in Neural Information Processing Systems 7

1995 599 citations G. Tesauro, David S. Touretzky et al. profile →
Temporal Difference Learning and TD-Gammon

1995 522 citations G. Tesauro ICGA Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
G. Tesauro United States	15	1.1k	697	530	230	174	22	2.2k
Marco Saerens Belgium	24	1.2k 1.1×	252 0.4×	503 0.9×	344 1.5×	185 1.1×	84	2.5k
Marcus Frean New Zealand	22	1.2k 1.1×	222 0.3×	298 0.6×	389 1.7×	161 0.9×	70	2.4k
Dennis M. Ritchie United States	19	1.3k 1.2×	1.7k 2.4×	691 1.3×	150 0.7×	236 1.4×	29	3.7k
Jun Long China	25	889 0.8×	688 1.0×	371 0.7×	442 1.9×	125 0.7×	178	2.5k
Alessandro Sperduti Italy	26	1.8k 1.7×	258 0.4×	381 0.7×	658 2.9×	310 1.8×	176	2.8k
Wesley W. Chu United States	31	1.1k 1.0×	1.2k 1.8×	509 1.0×	306 1.3×	839 4.8×	159	2.7k
Kumar Chellapilla United States	23	1.2k 1.1×	210 0.3×	634 1.2×	544 2.4×	391 2.2×	60	2.3k
Kensuke Fukuda Japan	26	1.2k 1.1×	2.1k 3.0×	387 0.7×	197 0.9×	390 2.2×	304	3.2k
David Powers Australia	26	849 0.8×	254 0.4×	179 0.3×	500 2.2×	307 1.8×	167	2.4k
David F. Gleich United States	26	1.3k 1.2×	538 0.8×	343 0.6×	490 2.1×	174 1.0×	92	3.0k

Countries citing papers authored by G. Tesauro

Since Specialization

Citations

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

Fields of papers citing papers by G. Tesauro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Tesauro

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Tesauro, G., David Gondek, Jonathan Lenchner, Jialu Fan, & John Prager. (2012). Simulation, learning, and optimization techniques in Watson's game strategies. IBM Journal of Research and Development. 56(3.4). 16:1–16:11. 10 indexed citations

2.

Tesauro, G., Nicholas K. Jong, R. Das, & Mohamed N. Bennani. (2006). A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation. 65–73. 230 indexed citations

3.

Tesauro, G., R. Das, William E. Walsh, & Jeffrey O. Kephart. (2005). Utility-Function-Driven Resource Allocation in Autonomic Systems. 342–343. 58 indexed citations

4.

Walsh, William E., G. Tesauro, Jeffrey O. Kephart, & R. Das. (2004). Utility functions in autonomic systems. 70–77. 283 indexed citations

5.

Tesauro, G.. (2003). Efficient search techniques for multi-attribute bilateral negotiation strategies. iii. 30–36. 9 indexed citations

6.

Hanson, J.E., et al.. (2003). Multi-agent implementation of asymmetric protocol for bilateral negotiations (extended abstract). 224–225. 3 indexed citations

7.

Sridharan, Manu & G. Tesauro. (2002). Multi-agent Q-learning and regression trees for automated pricing decisions. 447–448. 19 indexed citations

8.

Tesauro, G., Jeffrey O. Kephart, & Gregory B. Sorkin. (1996). Neural networks for computer virus recognition. IEEE Expert. 11(4). 5–6. 92 indexed citations

9.

Tesauro, G.. (1995). Temporal Difference Learning and TD-Gammon. ICGA Journal. 18(2). 88–88. 522 indexed citations breakdown →

10.

Tesauro, G., David S. Touretzky, & Todd K. Leen. (1995). Advances in Neural Information Processing Systems 7. 599 indexed citations breakdown →

11.

Cowan, Jack D., G. Tesauro, & J. Alspector. (1993). Proceedings of the 6th International Conference on Neural Information Processing Systems. 1 indexed citations

12.

Wejchert, Jakub & G. Tesauro. (1991). Visualizing processes in neural networks. IBM Journal of Research and Development. 35(1.2). 244–253. 14 indexed citations

13.

Tesauro, G.. (1990). Neurogammon: a neural-network backgammon program. 33–39 vol.3. 38 indexed citations

14.

Tesauro, G. & Terrence J. Sejnowski. (1989). A parallel network that learns to play backgammon. Artificial Intelligence. 39(3). 357–390. 78 indexed citations

15.

Tesauro, G.. (1988). A plausible neural circuit for classical conditioning without synaptic plasticity.. Proceedings of the National Academy of Sciences. 85(8). 2830–2833. 11 indexed citations

16.

Tesauro, G. & M. C. Cross. (1987). Grain boundaries in models of convective patterns. Philosophical magazine. A/Philosophical magazine. A. Physics of condensed matter. Structure, defects and mechanical properties. 56(6). 703–724. 17 indexed citations

17.

Cross, M. C., G. Tesauro, & Henry Greenside. (1986). Wavebumber selection and persistent dynamics in models of convection. Physica D Nonlinear Phenomena. 23(1-3). 12–18. 16 indexed citations

18.

Tesauro, G. & M. C. Cross. (1986). Climbing of dislocations in nonequilibrium patterns. Physical review. A, General physics. 34(2). 1363–1379. 46 indexed citations

19.

Glasser, A. H., S.C. Jardin, & G. Tesauro. (1984). Numerical solution of the resistive magnetohydrodynamic boundary layer equations. The Physics of Fluids. 27(5). 1225–1242. 35 indexed citations

20.

Mansfield, D. K., et al.. (1981). Effects of passive isolation on several optically pumped far-infrared laser lines. Optics Letters. 6(5). 230–230. 8 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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