21 citations · 93 across the 20 of their papers we have counts for
5 papers · 1 filter
Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future
Yan Song, He Jiang, Haifeng Zhang +3
Even though Google Research Football (GRF) was initially benchmarked and studied as a single-agent environment in its original paper, recent years have witnessed an increasing focu…
TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning
Qirui Mi, Siyu Xia, Yan Song +3
Taxation and government spending are crucial tools for governments to promote economic growth and maintain social equity. However, the difficulty in accurately predicting the dynam…
Joint Generative-Contrastive Representation Learning for Anomalous Sound Detection
Xiao-Min Zeng, Yan Song, Zhu Zhuo +5
In this paper, we propose a joint generative and contrastive representation learning method (GeCo) for anomalous sound detection (ASD). GeCo exploits a Predictive AutoEncoder (PAE)…
An Empirical Study on Google Research Football Multi-agent Scenarios
Yan Song, He Jiang, Zheng Tian +6
Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open…
AST-SED: An Effective Sound Event Detection Method Based on Audio Spectrogram Transformer
Kang Li, Yan Song, Li-Rong Dai +3
In this paper, we propose an effective sound event detection (SED) method based on the audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for audio t…