10 citations · 12 across the 11 of their papers we have counts for
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cs.MA2024
Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning
Dom Huh, Prasant Mohapatra
Sample efficiency remains a key challenge in multi-agent reinforcement learning (MARL). A promising approach is to learn a meaningful latent representation space through auxiliary…
cs.MA2023★ 10 cited
Multi-agent Reinforcement Learning: A Comprehensive Survey
Dom Huh, Prasant Mohapatra
Multi-agent systems (MAS) are widely prevalent and crucially important in numerous real-world applications, where multiple agents must make decisions to achieve their objectives in…
cs.MA2023
Decentralized Multi-agent Filtering
Dom Huh, Prasant Mohapatra
This paper addresses the considerations that comes along with adopting decentralized communication for multi-agent localization applications in discrete state spaces. In this frame…