61 citations · 63 across the 6 of their papers we have counts for
6 papers
You Only Align Once: Propagating Cooperative Behaviors in Multi-Agent Systems through Seed Agents
Nicole Hsing, Nicole Summer Hsing, Asuka Yuxi Zheng +4
Ensuring aligned agent behaviors in distributed open multi-agent systems remains challenging, especially as populations grow and unaligned agents may exist. We show that a single a…
Multi-Scenario Combination Based on Multi-Agent Reinforcement Learning to Optimize the Advertising Recommendation System
Yang Zhao, Chang Zhou, Jin Cao +4
This paper explores multi-scenario optimization on large platforms using multi-agent reinforcement learning (MARL). We address this by treating scenarios like search, recommendatio…
Simplified Temporal Consistency Reinforcement Learning
Yi Zhao, Wenshuai Zhao, Rinu Boney +2
Reinforcement learning is able to solve complex sequential decision-making tasks but is currently limited by sample efficiency and required computation. To improve sample efficienc…
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
Yi Zhao, Rinu Boney, Alexander Ilin +2
Offline reinforcement learning, by learning from a fixed dataset, makes it possible to learn agent behaviors without interacting with the environment. However, depending on the qua…
Continuous Monte Carlo Graph Search
Kalle Kujanpää, Amin Babadi, Yi Zhao +3
Online planning is crucial for high performance in many complex sequential decision-making tasks. Monte Carlo Tree Search (MCTS) employs a principled mechanism for trading off expl…
A General Deep Learning Framework for Network Reconstruction and Dynamics Learning
Zhang Zhang, Yi Zhao, Jing Liu +4
Many complex processes can be viewed as dynamical systems on networks. However, in real cases, only the performances of the system are known, the network structure and the dynamica…