Justin A. Boyan

2.5k citations
19 papers · 1.5k indexed · h-index 14
Topics
Evolutionary Algorithms and Applications (5 papers)Reinforcement Learning in Robotics (4 papers)Auction Theory and Applications (4 papers)
Partner nations
United StatesFrance

In The Last Decade

Justin A. Boyan

19 papers receiving 1.4k citations

Peers

Justin A. Boyan
Comparison fields: 5 of 84
  • Artificial Intelligence 854
  • Computer Networks and Communications 566
  • Computational Theory and Mathematics 274
  • Electrical and Electronic Engineering 263
  • Management Science and Operations Research 254
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Citations per field
00.5×4.9×
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Citations per year

Countries citing papers authored by Justin A. Boyan

Since Specialization
Citations

This map shows the geographic impact of Justin A. Boyan'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 Justin A. Boyan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin A. Boyan more than expected).

Fields of papers citing papers by Justin A. Boyan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Justin A. Boyan. 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 Justin A. Boyan. The network helps show where Justin A. Boyan may publish in the future.

Co-authorship network of co-authors of Justin A. Boyan

This figure shows the co-authorship network connecting the top 25 collaborators of Justin A. Boyan. A scholar is included among the top collaborators of Justin A. Boyan 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 Justin A. Boyan. Justin A. Boyan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1
Bidding Algorithms for Simultaneous Auctions: A Case Study
18
2 22
3 14
4 187
5 3
6 29
7 9
8
Exact Solutions to Time-Dependent MDPs
70
9
IMPROVED RESULTS FOR ROUTE PLANNING IN STOCHASTIC TRANSPORTATION NETWORKS
13
10
A Machine Learning Architecture for Optimizing Web Search Engines
79
11
Least-Squares Temporal Difference Learning
152
12
Learning evaluation functions for global optimization and Boolean satisfiability
47
13
Value Function Based Production Scheduling
20
14
Learning evaluation functions for global optimization
41
15
Using Prediction to Improve Combinatorial Optimization Search
5
16
Learning evaluation functions for large acyclic domains
12
17
Generalization in Reinforcement Learning: Safely Approximating the Value Function
326
18
Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach
490
19
Modular Neural Networks for Learning Context-Dependent Game Strategies
9

About Justin A. Boyan

Justin A. Boyan is a scholar working on Management Science and Operations Research, Industrial and Manufacturing Engineering and Marketing, having authored 19 papers that have together received 1.5k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (5 papers), Reinforcement Learning in Robotics (4 papers) and Auction Theory and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (854 citations), Computer Networks and Communications (566 citations) and Management Science and Operations Research (254 citations). Justin A. Boyan has collaborated with scholars based in United States and France. Frequent co-authors include Michael L. Littman, Andrew Moore, Dayne Freitag, Amy Greenwald, Andrew W. Moore, Scott E. Fahlman, Jeff Schneider and Michael Mitzenmacher. Their work appears in journals such as Machine Learning, Autonomous Agents and Multi-Agent Systems and arXiv (Cornell University).

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.

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