4.8k citations · 5.1k across the 44 of their papers we have counts for
4 papers · 1 filter
CREW-WILDFIRE: Benchmarking Agentic Multi-Agent Collaborations at Scale
Jonathan Hyun, Nicholas R Waytowich, Boyuan Chen
Despite rapid progress in large language model (LLM)-based multi-agent systems, current benchmarks fall short in evaluating their scalability, robustness, and coordination capabili…
On Memory Mechanism in Multi-Agent Reinforcement Learning
Yilun Zhou, Derrik E. Asher, Nicholas R. Waytowich +1
Multi-agent reinforcement learning (MARL) extends (single-agent) reinforcement learning (RL) by introducing additional agents and (potentially) partial observability of the environ…
Coordination-driven learning in multi-agent problem spaces
Sean L. Barton, Nicholas R. Waytowich, Derrik E. Asher
We discuss the role of coordination as a direct learning objective in multi-agent reinforcement learning (MARL) domains. To this end, we present a novel means of quantifying coordi…
Measuring collaborative emergent behavior in multi-agent reinforcement learning
Sean L. Barton, Nicholas R. Waytowich, Erin Zaroukian +1
Multi-agent reinforcement learning (RL) has important implications for the future of human-agent teaming. We show that improved performance with multi-agent RL is not a guarantee o…