Robert H. Crites
About
In The Last Decade
Robert H. Crites
7 papers receiving 639 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 419
- Control and Systems Engineering 195
- Management Science and Operations Research 171
- Sociology and Political Science 94
- Computational Theory and Mathematics 86
Countries citing papers authored by Robert H. Crites
This map shows the geographic impact of Robert H. Crites'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 Robert H. Crites with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert H. Crites more than expected).
Fields of papers citing papers by Robert H. Crites
This network shows the impact of papers produced by Robert H. Crites. 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 Robert H. Crites. The network helps show where Robert H. Crites may publish in the future.
Co-authorship network of co-authors of Robert H. Crites
This figure shows the co-authorship network connecting the top 25 collaborators of Robert H. Crites. A scholar is included among the top collaborators of Robert H. Crites 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 Robert H. Crites. Robert H. Crites is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 176 | |
| 4 | 207 | |
| 5 | Large-scale dynamic optimization using teams of reinforcement learning agents | 15 |
| 6 | Improving Elevator Performance Using Reinforcement Learning | 318 |
| 7 | An Actor/Critic Algorithm that is Equivalent to Q-Learning | 16 |
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.