This map shows the geographic impact of David Abel'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 David Abel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Abel more than expected).
This network shows the impact of papers produced by David Abel. 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 David Abel. The network helps show where David Abel may publish in the future.
Co-authorship network of co-authors of David Abel
This figure shows the co-authorship network connecting the top 25 collaborators of David Abel.
A scholar is included among the top collaborators of David Abel 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 David Abel. David Abel 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
1.
Abel, David. (2024). Selection in molecular evolution. Studies in History and Philosophy of Science Part A. 107. 54–63.2 indexed citations
Abel, David, et al.. (2020). Value Preserving State-Action Abstractions. International Conference on Artificial Intelligence and Statistics. 1639–1650.7 indexed citations
4.
Abel, David, et al.. (2019). Finding Options that Minimize Planning Time.. International Conference on Machine Learning. 3120–3129.2 indexed citations
5.
Abel, David, et al.. (2019). Discovering Options for Exploration by Minimizing Cover Time. International Conference on Machine Learning. 3130–3139.2 indexed citations
6.
Abel, David. (2019). simple_rl: Reproducible Reinforcement Learning in Python.. International Conference on Learning Representations.3 indexed citations
7.
Ho, Mark K., David Abel, Thomas L. Griffiths, & Michael L. Littman. (2019). The value of abstraction. Current Opinion in Behavioral Sciences. 29. 111–116.17 indexed citations
8.
Abel, David, et al.. (2018). Policy and Value Transfer in Lifelong Reinforcement Learning. International Conference on Machine Learning. 20–29.17 indexed citations
9.
Abel, David, et al.. (2018). State Abstractions for Lifelong Reinforcement Learning. International Conference on Machine Learning. 10–19.32 indexed citations
10.
Abel, David, et al.. (2018). Bandit-Based Solar Panel Control. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1).2 indexed citations
Barth-Maron, Gabriel, David Abel, James MacGlashan, & Stefanie Tellex. (2014). Affordances as Transferable Knowledge for Planning Agents.. National Conference on Artificial Intelligence.5 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.