Akshat Kumar

846 citations
67 papers · 543 · h-index 14

Impact in

Papers in

Akshat Kumar

57 papers receiving 523 citations

Peers

Akshat Kumar
Comparison fields: 5 of 79
  • Transportation 70
  • Management Science and Operations Research 95
  • Industrial and Manufacturing Engineering 70
  • Artificial Intelligence 225
  • Automotive Engineering 76
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Citations per field
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Citations per year

Countries citing papers authored by Akshat Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Akshat Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akshat Kumar. 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 Akshat Kumar. The network helps show where Akshat Kumar may publish in the future.

Co-authors

The 25 scholars most cited alongside Akshat Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Akshat Kumar Line = papers co-authored together Akshat Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200947
2 202245
3
Credit Assignment For Collective Multiagent RL With Global Rewards
201832
4 201331
5 200928
6 201026
7
Approximate Inference in Collective Graphical Models
201324
8 201524
9 201724
10
Message Passing for Collective Graphical Models
201517
11 201916
12 201815
13 201813
14
Dynamic Programming Approximations for Partially Observable Stochastic Games
200913
15
H-DPOP: using hard constraints for search space pruning in DCOP
200812
16 200712
17 201810
18
Event-detecting multi-agent MDPs: complexity and constant-factor approximation
200910
19 20169
20 20188

About Akshat Kumar

Akshat Kumar is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Control and Systems Engineering and Computational Theory and Mathematics, having authored 67 papers that have together received 543 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (12 papers), Reinforcement Learning in Robotics (12 papers), Auction Theory and Applications (11 papers), Machine Learning and Algorithms (7 papers), Transportation and Mobility Innovations (6 papers), Constraint Satisfaction and Optimization (6 papers), Transportation Planning and Optimization (5 papers) and Formal Methods in Verification (5 papers). The work is most often cited by research in Transportation (70 citations), Management Science and Operations Research (95 citations), Industrial and Manufacturing Engineering (70 citations), Artificial Intelligence (225 citations) and Automotive Engineering (76 citations). Akshat Kumar has collaborated with scholars based in Singapore, United States and India. Frequent co-authors include Shlomo Zilberstein, Hoong Chuin Lau, Pradeep Varakantham, Duc Thien Nguyen, Adrian Petcu, Boi Faltings, Daniel Sheldon, Marc Toussaint, Shivashankar B. Nair and Michael T. Lu. Their work appears in journals such as ACM Transactions on Intelligent Systems and Technology, Journal of Physics A Mathematical and Theoretical, Journal of Artificial Intelligence Research, Lecture notes in computer science and Lecture notes in electrical engineering.

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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