Reinforcement Learning in Agent-Based Market Simulation: Unveiling Realistic Stylized Facts and Behavior

no code implementations • 28 Mar 2024 • Zhiyuan Yao, Zheng Li, Matthew Thomas, Ionut Florescu

Investors and regulators can greatly benefit from a realistic market simulator that enables them to anticipate the consequences of their decisions in real markets.

Reinforcement Learning (RL)

The FinBen: An Holistic Financial Benchmark for Large Language Models

2 code implementations • 20 Feb 2024 • Qianqian Xie, Weiguang Han, Zhengyu Chen, Ruoyu Xiang, Xiao Zhang, Yueru He, Mengxi Xiao, Dong Li, Yongfu Dai, Duanyu Feng, Yijing Xu, Haoqiang Kang, Ziyan Kuang, Chenhan Yuan, Kailai Yang, Zheheng Luo, Tianlin Zhang, Zhiwei Liu, Guojun Xiong, Zhiyang Deng, Yuechen Jiang, Zhiyuan Yao, Haohang Li, Yangyang Yu, Gang Hu, Jiajia Huang, Xiao-Yang Liu, Alejandro Lopez-Lira, Benyou Wang, Yanzhao Lai, Hao Wang, Min Peng, Sophia Ananiadou, Jimin Huang

This along with the rapid development of LLMs, highlights the urgent need for a systematic financial evaluation benchmark for LLMs.

Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach

no code implementations • 1 Feb 2024 • Zhiyuan Yao, Ionut Florescu, Chihoon Lee

In this paper we are introducing a new reinforcement learning method for control problems in environments with delayed feedback.

Atari Games Model-based Reinforcement Learning +1

Develop End-to-End Anomaly Detection System

no code implementations • 1 Feb 2024 • Emanuele Mengoli, Zhiyuan Yao, Wutao Wei

To address this challenge, in this paper, we propose an end-to-end anomaly detection model development pipeline.

Anomaly Detection

A Hybrid Approach for Smart Alert Generation

no code implementations • 2 Jun 2023 • Yao Zhao, Sophine Zhang, Zhiyuan Yao

Anomaly detection is an important task in network management.

Anomaly Detection Feature Engineering +2

Towards Modern Card Games with Large-Scale Action Spaces Through Action Representation

no code implementations • 25 Jun 2022 • Zhiyuan Yao, Tianyu Shi, Site Li, Yiting Xie, Yuanyuan Qin, Xiongjie Xie, Huan Lu, Yan Zhang

Axie infinity is a complicated card game with a huge-scale action space.

Card Games reinforcement-learning +1

Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game

1 code implementation • 3 Jun 2022 • Zhiyuan Yao, Zihan Ding

A fully distributed MARL algorithm is proposed to approximate the Nash equilibrium of the game.

Fairness Management +1

Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center

no code implementations • 27 Jan 2022 • Zhiyuan Yao, Zihan Ding, Thomas Clausen

This paper presents the network load balancing problem, a challenging real-world task for multi-agent reinforcement learning (MARL) methods.

Multi-agent Reinforcement Learning reinforcement-learning +1

Reinforced Workload Distribution Fairness

no code implementations • 29 Oct 2021 • Zhiyuan Yao, Zihan Ding, Thomas Heide Clausen

Network load balancers are central components in data centers, that distributes workloads across multiple servers and thereby contribute to offering scalable services.

Fairness Reinforcement Learning (RL)

Towards Intelligent Load Balancing in Data Centers

1 code implementation • 27 Oct 2021 • Zhiyuan Yao, Yoann Desmouceaux, Mark Townsley, Thomas Heide Clausen

This paper proposes Aquarius to bridge the gap between ML and networking systems and demonstrates its usage in the context of network load balancers.