Charles L. Isbell

3.7k citations
105 papers · 2.0k indexed · h-index 22
Topics
Reinforcement Learning in Robotics (34 papers)Artificial Intelligence in Games (18 papers)Context-Aware Activity Recognition Systems (11 papers)

In The Last Decade

Charles L. Isbell

100 papers receiving 1.8k citations

Peers

Charles L. Isbell
Comparison fields: 5 of 117
  • Artificial Intelligence 1.4k
  • Computer Vision and Pattern Recognition 419
  • Control and Systems Engineering 295
  • Signal Processing 226
  • Sociology and Political Science 161
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Countries citing papers authored by Charles L. Isbell

Since Specialization
Citations

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

Fields of papers citing papers by Charles L. Isbell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles L. Isbell. 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 Charles L. Isbell. The network helps show where Charles L. Isbell may publish in the future.

Co-authorship network of co-authors of Charles L. Isbell

This figure shows the co-authorship network connecting the top 25 collaborators of Charles L. Isbell. A scholar is included among the top collaborators of Charles L. Isbell 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 Charles L. Isbell. Charles L. Isbell 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
#WorkIndexed citations
1 3
2
Policy shaping with human teachers
36
3
Policy Shaping: Integrating Human Feedback with Reinforcement Learning
166
4
Markov games of incomplete information for multi-agent reinforcement learning
6
5
Transfer learning in real-time strategy games using hybrid CBR/RL
75
6
Ultrafast Monte Carlo for kernel estimators and generalized statistical summations
6
7
Managing domain knowledge and multiple models with boosting
1
8 7
9
Improving activity discovery with automatic neighborhood estimation
34
10
Wavelet Statistics for Human Motion Classification.
2
11
Targeting specific distributions of trajectories in MDPs
36
12
On the difficulty of modular reinforcement learning for real-world partial programming
15
13
Unsupervised activity discovery and characterization from event-streams
19
14 2
15
Cobot: A Social Reinforcement Learning Agent
19
16
Cobot in LambdaMOO: A Social Statistics Agent
41
17
Restructuring Sparse High Dimensional Data for Effective Retrieval
37
18
MIMIC: Finding Optima by Estimating Probability Densities
299
19
Reasoning with Black Boxes: Handling Test Concepts in CLASSIC
3
20
Description logic in practice: a CLASSIC application
18

About Charles L. Isbell

Charles L. Isbell is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 105 papers that have together received 2.0k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (34 papers), Artificial Intelligence in Games (18 papers) and Context-Aware Activity Recognition Systems (11 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Computer Science Applications (143 citations) and Signal Processing (226 citations). Charles L. Isbell has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Paul Viola, Jeremy S. De Bonet, Andrea L. Thomaz, Irfan Essa, K.A. Subramanian, David Minnen, Thad Starner, Jonathan Scholz, Michael Mateas and David L. Roberts. Their work appears in journals such as Proceedings of the IEEE, Communications of the ACM and Artificial Intelligence.

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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