Maulik Shah
Papers
1
Total Citations
11
H-Index
1
About
Maulik Shah is a researcher advancing the frontiers of multiagent systems and decision-theoretic planning. His work addresses the critical challenge of scalability in open and typed multiagent environments—where the composition of agents changes dynamically over time. In his most-cited paper, "Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems" (2020, 11 citations), Shah introduces novel frameworks that enable autonomous agents to plan effectively even when teammates or competitors may unpredictably enter or leave the system. This has direct implications for real-world applications like collaborative robotics in disaster response, where agents (e.g., firefighting drones) may become temporarily unavailable due to resource depletion. By modeling agent types and openness, Shah’s contributions help bridge the gap between theoretical multiagent planning and practical, deployable systems. His work is foundational for researchers tackling coordination in dynamic, uncertain environments. With a growing citation impact, Shah is establishing himself as a key voice in making multiagent systems more robust, adaptive, and scalable for complex, real-world tasks.
Research Focus
Key Achievements
Top Papers
- 1Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems11 citations · 2020