23 citations · 58 across the 35 of their papers we have counts for
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cs.MA2021
Status-quo policy gradient in Multi-Agent Reinforcement Learning
Pinkesh Badjatiya, Mausoom Sarkar, Nikaash Puri +4
Individual rationality, which involves maximizing expected individual returns, does not always lead to high-utility individual or group outcomes in multi-agent problems. For instan…
cs.MA2021★ 1 cited
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks
Ayush Chopra, Esma Gel, Jayakumar Subramanian +5
We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent…