Milind Tambe
Impact in
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- Game Theory and Applications
- Computer Networks and Communications top 0.2%
- Constraint Satisfaction and Optimization
Papers in
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- Game Theory and Applications 37
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- Multi-Agent Systems and Negotiation 70
- AI-based Problem Solving and Planning 57
- Reinforcement Learning in Robotics 49
- Logic, Reasoning, and Knowledge 33
- Co-authors
- Makoto YokooDavid V. PynadathJonathan P. PearceFernando OrdóñezSarit KrausChristopher KiekintveldPragnesh Jay ModiPradeep Varakantham
- Journals
- AI Magazine (16 papers)Autonomous Agents and Multi-Agent Systems (12 papers)Artificial Intelligence (6 papers)Journal of Artificial Intelligence Research (3 papers)Cognitive Science (3 papers)
- Partner nations
- United StatesSingaporeIsrael
In The Last Decade
Milind Tambe
424 papers receiving 9.8k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Management Science and Operations Research 2.1k
- Computer Networks and Communications 3.4k
- Artificial Intelligence 3.7k
- Signal Processing 996
- Civil and Structural Engineering 1.8k
Countries citing papers authored by Milind Tambe
This map shows the geographic impact of Milind Tambe'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 Milind Tambe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Milind Tambe more than expected).
Fields of papers citing papers by Milind Tambe
This network shows the impact of papers produced by Milind Tambe. 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 Milind Tambe. The network helps show where Milind Tambe may publish in the future.
Co-authors
The 25 scholars most cited alongside Milind Tambe, 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 | 2024 | 1 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 3 | |
| 6 | 2021 | 6 | |
| 7 | 2021 | 6 | |
| 8 | 2021 | 1 | |
| 9 | 2020 | 2 | |
| 10 | 2020 | 1 | |
| 11 | 2020 | 16 | |
| 12 | 2019 | 1 | |
| 13 | 2019 | 3 | |
| 14 | Learning policies for Social network discovery with Reinforcement learning. | 2019 | 1 |
| 15 | 2018 | 12 | |
| 16 | 2018 | 34 | |
| 17 | 2018 | 24 | |
| 18 | 2013 | 37 | |
| 19 | 2009 | 2 | |
| 20 | 2005 | 1 |
About Milind Tambe
Milind Tambe is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computer Networks and Communications, Civil and Structural Engineering and Ocean Engineering, having authored 448 papers that have together received 10.5k indexed citations. Recurring topics across this work include Infrastructure Resilience and Vulnerability Analysis (98 papers), Multi-Agent Systems and Negotiation (70 papers), AI-based Problem Solving and Planning (57 papers), Constraint Satisfaction and Optimization (54 papers), Reinforcement Learning in Robotics (49 papers), Evacuation and Crowd Dynamics (44 papers), Game Theory and Applications (37 papers) and Logic, Reasoning, and Knowledge (33 papers). The work is most often cited by research in Management Science and Operations Research (2.1k citations), Computer Networks and Communications (3.4k citations), Artificial Intelligence (3.7k citations), Signal Processing (996 citations) and Civil and Structural Engineering (1.8k citations). Milind Tambe has collaborated with scholars based in United States, Singapore and Israel. Frequent co-authors include Makoto Yokoo, David V. Pynadath, Jonathan P. Pearce, Fernando Ordóñez, Sarit Kraus, Christopher Kiekintveld, Pragnesh Jay Modi, Pradeep Varakantham, Wei‐Min Shen and Janusz Marecki. Their work appears in journals such as AI Magazine, Autonomous Agents and Multi-Agent Systems, Artificial Intelligence, Journal of Artificial Intelligence Research and Cognitive Science.
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.