This map shows the geographic impact of Daniel Bryce'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 Daniel Bryce with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Bryce more than expected).
This network shows the impact of papers produced by Daniel Bryce. 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 Daniel Bryce. The network helps show where Daniel Bryce may publish in the future.
Co-authorship network of co-authors of Daniel Bryce
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Bryce.
A scholar is included among the top collaborators of Daniel Bryce 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 Daniel Bryce. Daniel Bryce is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bryce, Daniel, Sicun Gao, David J. Musliner, & Robert P. Goldman. (2015). SMT-Based Nonlinear PDDL+ Planning. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1).33 indexed citations
Bryce, Daniel. (2012). Scaffolding in teaching knowledge representation. Journal of computing sciences in colleges. 28(2). 25–31.1 indexed citations
9.
Freed, Michael, et al.. (2011). Interactive bootstrapped learning for end-user programming. National Conference on Artificial Intelligence. 27–32.2 indexed citations
10.
Bryce, Daniel. (2011). Wumpus World in introductory artificial intelligence. Journal of computing sciences in colleges. 27(2). 58–65.1 indexed citations
Mailler, Roger, et al.. (2009). MABLE: a framework for learning from natural instruction. Adaptive Agents and Multi-Agents Systems. 393–400.4 indexed citations
13.
Bryce, Daniel, et al.. (2008). International Planning Competition Uncertainty Part: Benchmarks and Results.17 indexed citations
Bryce, Daniel, Subbarao Kambhampati, & David E. Smith. (2006). Sequential monte carlo in probabilistic planning reachability heuristics. International Conference on Automated Planning and Scheduling. 233–242.18 indexed citations
17.
Bryce, Daniel, et al.. (2005). State agnostic planning graphs and the application to belief-space planning. National Conference on Artificial Intelligence. 1131–1138.6 indexed citations
18.
Bryce, Daniel & Subbarao Kambhampati. (2004). Heuristic guidance measures for conformant planning. International Conference on Automated Planning and Scheduling. 365–374.18 indexed citations
19.
Bryce, Daniel, Subbarao Kambhampati, & David E. Smith. (2004). Planning in belief space with a labelled uncertainty graph. National Conference on Artificial Intelligence. 1–6.6 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.