Ahmed Khalifa
About
In The Last Decade
Ahmed Khalifa
35 papers receiving 459 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 360
- Sociology and Political Science 200
- Computer Vision and Pattern Recognition 158
- Developmental and Educational Psychology 92
- Control and Systems Engineering 61
Countries citing papers authored by Ahmed Khalifa
This map shows the geographic impact of Ahmed Khalifa'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 Ahmed Khalifa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed Khalifa more than expected).
Fields of papers citing papers by Ahmed Khalifa
This network shows the impact of papers produced by Ahmed Khalifa. 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 Ahmed Khalifa. The network helps show where Ahmed Khalifa may publish in the future.
Co-authorship network of co-authors of Ahmed Khalifa
This figure shows the co-authorship network connecting the top 25 collaborators of Ahmed Khalifa. A scholar is included among the top collaborators of Ahmed Khalifa 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 Ahmed Khalifa. Ahmed Khalifa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 76 | |
| 7 | 1 | |
| 8 | "Superstition" in the Network:Deep Reinforcement Learning Plays Deceptive Games | 2 |
| 9 | 6 | |
| 10 | 72 | |
| 11 | 3 | |
| 12 | Procedural Level Generation Improves Generality of Deep Reinforcement Learning | 7 |
| 13 | 41 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 29 | |
| 17 | Modifying MCTS for human-like general video game playing | 29 |
| 18 | 2 | |
| 19 | 5 | |
| 20 | Design and Implementation of a Port Simulator Using Formal Graphical Approach (FGA) | 2 |
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.