Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments
2010660 citationsDmitri Dolgov, Sebastian Thrun et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Dmitri Dolgov'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 Dmitri Dolgov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitri Dolgov more than expected).
This network shows the impact of papers produced by Dmitri Dolgov. 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 Dmitri Dolgov. The network helps show where Dmitri Dolgov may publish in the future.
Co-authorship network of co-authors of Dmitri Dolgov
This figure shows the co-authorship network connecting the top 25 collaborators of Dmitri Dolgov.
A scholar is included among the top collaborators of Dmitri Dolgov 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 Dmitri Dolgov. Dmitri Dolgov 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.
Dolgov, Dmitri. (2018). Moments of Structure Functions in Full QCD. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).1 indexed citations
2.
Hendler, James, Philipp Cimiano, Dmitri Dolgov, et al.. (2008). AI's 10 to Watch. IEEE Intelligent Systems. 23(3). 9–19.2 indexed citations
James, M. R., et al.. (2007). Improving anytime point-based value iteration using principled point selections. International Joint Conference on Artificial Intelligence. 865–870.1 indexed citations
Musliner, David J., et al.. (2006). Coordinated Plan Management Using Multiagent MDPs. National Conference on Artificial Intelligence. 73–80.31 indexed citations
8.
Dolgov, Dmitri & Edmund H. Durfee. (2006). Symmetric primal-dual approximate linear programming for factored MDPs.6 indexed citations
9.
Dolgov, Dmitri. (2006). Integrated Resource Allocation and Planning in Stochastic Multiagent Environments. Deep Blue (University of Michigan).
Dolgov, Dmitri & Edmund H. Durfee. (2005). Stationary deterministic policies for constrained MDPs with multiple rewards, costs, and discount factors. International Joint Conference on Artificial Intelligence. 1326–1331.34 indexed citations
Dolgov, Dmitri & Edmund H. Durfee. (2004). Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes.. Annals of Mathematics and Artificial Intelligence.5 indexed citations
17.
Dolgov, Dmitri & Edmund H. Durfee. (2004). Optimal resource allocation and policy formulation in loosely-coupled Markov decision processes. International Conference on Automated Planning and Scheduling. 315–324.28 indexed citations
18.
Dolgov, Dmitri & Edmund H. Durfee. (2003). Approximating optimal policies for agents with limited execution resources. International Joint Conference on Artificial Intelligence. 1107–1112.14 indexed citations
19.
Dolgov, Dmitri. (2000). Calculation of the structure of the proton using lattice QCD. 2777.1 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.