Jonathan Sorg
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Artificial Intelligence in Games
- Machine Learning and Algorithms
-
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
Papers in
-
- Reinforcement Learning in Robotics 7
- Machine Learning and Algorithms 3
- Evolutionary Algorithms and Applications 2
- Artificial Intelligence in Games 1
-
- Advanced Bandit Algorithms Research 2
- Auction Theory and Applications 1
- Co-authors
- Satinder Singh (6 shared papers)Richard L. Lewis (6 shared papers)Andrew G. Barto (1 shared paper)Satinder Singh (2 shared papers)
- Journals
- Neural Information Processing Systems (1 paper)International Conference on Machine Learning (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Adaptive Agents and Multi-Agents Systems (3 papers)Uncertainty in Artificial Intelligence (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Jonathan Sorg
8 papers receiving 381 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 262
- Cognitive Neuroscience 87
- Management Science and Operations Research 58
- General Decision Sciences 6
- Experimental and Cognitive Psychology 34
Countries citing papers authored by Jonathan Sorg
This map shows the geographic impact of Jonathan Sorg'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 Jonathan Sorg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Sorg more than expected).
Fields of papers citing papers by Jonathan Sorg
This network shows the impact of papers produced by Jonathan Sorg. 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 Jonathan Sorg. The network helps show where Jonathan Sorg may publish in the future.
Co-authors
The 4 scholars most cited alongside Jonathan Sorg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 256 | |
| 2 | Reward Design via Online Gradient Ascent | 2010 | 39 |
| 3 | Internal Rewards Mitigate Agent Boundedness | 2010 | 32 |
| 4 | 2009 | 27 | |
| 5 | Variance-based rewards for approximate Bayesian reinforcement learning | 2010 | 15 |
| 6 | 2012 | 12 | |
| 7 | 2011 | 11 | |
| 8 | 2010 | 10 |
About Jonathan Sorg
Jonathan Sorg is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Management Information Systems and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 402 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Machine Learning and Algorithms (3 papers), Evolutionary Algorithms and Applications (2 papers), Advanced Bandit Algorithms Research (2 papers), Optimization and Search Problems (2 papers), Artificial Intelligence in Games (1 paper), Supply Chain and Inventory Management (1 paper) and Auction Theory and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (262 citations), Cognitive Neuroscience (87 citations), Management Science and Operations Research (58 citations), General Decision Sciences (6 citations) and Experimental and Cognitive Psychology (34 citations). Jonathan Sorg has collaborated with scholars based in United States and Israel. Frequent co-authors include Satinder Singh, Richard L. Lewis, Andrew G. Barto and Satinder Singh. Their work appears in journals such as Neural Information Processing Systems, International Conference on Machine Learning, Proceedings of the AAAI Conference on Artificial Intelligence, Adaptive Agents and Multi-Agents Systems and Uncertainty in 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.