Pablo Hernández-Leal

32 papers receiving 896 citations

Hit Papers

A survey and critique of multiagent deep reinforcement le...20192026202120232019100200300

Peers

Pablo Hernández-Leal
Comparison fields: 5 of 92
  • Artificial Intelligence 405
  • Electrical and Electronic Engineering 309
  • Control and Systems Engineering 230
  • Computer Networks and Communications 130
  • Management Science and Operations Research 82
Replace Syed Akhter Hossain with:
Syed Akhter Hossain Bangladesh
Yang Ji China
Gaspard Harerimana South Korea
Pervez Khan South Korea
Karen Zita Haigh United States
José Antonio Iglesias Spain
Peter Vrancx Belgium
Myeonghwi Kim South Korea
Cosmas Ifeanyi Nwakanma South Korea
Pablo Hernández-Leal relative to Syed Akhter Hossain Bangladesh Syed Akhter Hossain's profile →
Citations per field
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Citations per year

Countries citing papers authored by Pablo Hernández-Leal

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Hernández-Leal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pablo Hernández-Leal. 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 Pablo Hernández-Leal. The network helps show where Pablo Hernández-Leal may publish in the future.

Co-authorship network of co-authors of Pablo Hernández-Leal

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Hernández-Leal. A scholar is included among the top collaborators of Pablo Hernández-Leal 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 Pablo Hernández-Leal. Pablo Hernández-Leal 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
#WorkIndexed citations
1 3
2 31
3 13
4
A survey and critique of multiagent deep reinforcement learningbreakdown →
339
5 247
6
Is multiagent deep reinforcement learning the answer or the question? A brief survey
30
7 3
8
Learning on a Budget Using Distributional RL
1
9
Identifying and Tracking Switching, Non-Stationary Opponents: A Bayesian Approach
14
10 47
11 3
12 22
13 5
14 1
15
On the Estimation of Missing Data in Incomplete Databases: Autoregressive Bayesian Networks
4
16 5
17 6
18
Contrasting temporal Bayesian network models for analyzing HIV mutations
1
19 2
20
Learning Temporal Nodes Bayesian Networks
6

About Pablo Hernández-Leal

Pablo Hernández-Leal is a scholar working on Artificial Intelligence, Management Science and Operations Research and Applied Psychology, having authored 34 papers that have together received 946 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (17 papers), Bayesian Modeling and Causal Inference (6 papers) and Smart Grid Energy Management (6 papers). The work is most often cited by research in Artificial Intelligence (405 citations), Control and Systems Engineering (230 citations) and Management Science and Operations Research (82 citations). Pablo Hernández-Leal has collaborated with scholars based in Mexico, Netherlands and United States. Frequent co-authors include Matthew E. Taylor, Bilal Kartal, Michael Kaisers, Luis Enrique Sucar, João Soares, Fernando Lezama, Tiago Pinto, Zita Vale, Eduardo F. Morales and Enrique Muñoz de Cote. Their work appears in journals such as IEEE Transactions on Power Systems, Pattern Recognition and Pattern Recognition Letters.

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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