Edward Lockhart

1.3k total citations
4 papers, 57 citations indexed

About

Edward Lockhart is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Management Science and Operations Research. According to data from OpenAlex, Edward Lockhart has authored 4 papers receiving a total of 57 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Cognitive Neuroscience and 1 paper in Management Science and Operations Research. Recurrent topics in Edward Lockhart's work include Reinforcement Learning in Robotics (3 papers), Adversarial Robustness in Machine Learning (2 papers) and EEG and Brain-Computer Interfaces (1 paper). Edward Lockhart is often cited by papers focused on Reinforcement Learning in Robotics (3 papers), Adversarial Robustness in Machine Learning (2 papers) and EEG and Brain-Computer Interfaces (1 paper). Edward Lockhart collaborates with scholars based in United Kingdom, Canada and Brazil. Edward Lockhart's co-authors include David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Peter Battaglia, Oriol Vinyals, Murray Shanahan, Karl Tuyls, Vinícius Zambaldi and Timothy Lillicrap and has published in prestigious journals such as International Conference on Machine Learning, International Conference on Learning Representations and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Edward Lockhart

4 papers receiving 55 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Edward Lockhart United Kingdom	3	44	8	6	6	4	4	57
I. Babuschkin United States	3	45 1.0×	16 2.0×	5 0.8×	6 1.0×	4 1.0×	6	66
William H. Guss United States	3	33 0.8×	14 1.8×	3 0.5×	6 1.0×	5 1.3×	4	47
Aldo Pacchiano United States	4	53 1.2×	10 1.3×	2 0.3×	5 0.8×	6 1.5×	19	66
Jiri Hron United Kingdom	5	82 1.9×	28 3.5×	7 1.2×	4 0.7×	3 0.8×	8	104
Léonard Hussenot United States	4	40 0.9×	5 0.6×	10 1.7×	1 0.2×	4 1.0×	5	50
Noah Fiedel	2	29 0.7×	11 1.4×	5 0.8×	3 0.5×	1 0.3×	2	52
Kumar Shridhar Switzerland	7	75 1.7×	14 1.8×	5 0.8×	2 0.3×		13	98
Yafu Li China	6	77 1.8×	20 2.5×	4 0.7×	3 0.5×	2 0.5×	17	108
Edoardo Conti Denmark	2	41 0.9×	2 0.3×	4 0.7×	4 0.7×	14 3.5×	2	52
Ryo Kikuchi Japan	5	31 0.7×	3 0.4×	3 0.5×	2 0.3×	7 1.8×	10	38

Countries citing papers authored by Edward Lockhart

Since Specialization

Citations

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

Fields of papers citing papers by Edward Lockhart

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Lockhart

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

All Works

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4 of 4 papers shown

1.

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

2.

Lockhart, Edward, Elnaz Davoodi, Neil Burch, et al.. (2021). Solving Common-Payoff Games with Approximate Policy Iteration. Proceedings of the AAAI Conference on Artificial Intelligence. 35(11). 9695–9703. 3 indexed citations

3.

Munos, Rémi, Julien Pérolat, Jean-Baptiste Lespiau, et al.. (2020). Fast computation of Nash Equilibria in Imperfect Information Games. International Conference on Machine Learning. 1. 7119–7129. 1 indexed citations

4.

Zambaldi, Vinícius, David Raposo, Adam Santoro, et al.. (2018). Deep reinforcement learning with relational inductive biases. International Conference on Learning Representations. 47 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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