7 citations · 19 across the 8 of their papers we have counts for
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cs.MA2024★ 4 cited
Cooperation and Fairness in Multi-Agent Reinforcement Learning
Jasmine Jerry Aloor, Siddharth Nayak, Sydney Dolan +1
Multi-agent systems are trained to maximize shared cost objectives, which typically reflect system-level efficiency. However, in the resource-constrained environments of mobility a…
cs.RO2024★ 1 cited
LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments
Siddharth Nayak, Adelmo Morrison Orozco, Marina Ten Have +10
The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditio…