Name
Title | ||
|---|---|---|
MADES: A Unified Framework for Integrating Agent-Based Simulation with Multi-Agent Reinforcement Learning |
Abstract | ||
|---|---|---|
Agent-Based Simulation (ABS) provides distributed entities for simulating agent emergence or interactive behaviors, but the agent behaviors usually rely on the hard rules, thus lacking the intelligent decision-making capability. With the development of artificial intelligence, Multi-Agent Reinforcement Learning (MARL) has shown positive potential in robot control, autonomous driving, and human-mac... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.23919/ANNSIM52504.2021.9552052 | 2021 Annual Modeling and Simulation Conference (ANNSIM) |
Keywords | DocType | ISBN |
agent-based simulation,reinforcement learning,multi-agent system,discrete event simulation | Conference | 978-1-56555-375-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaohan Wang | 1 | 0 | 1.01 |
| Lin Zhang | 2 | 580 | 34.51 |
| Yuanjun Laili | 3 | 194 | 18.18 |
| Kunyu Xie | 4 | 0 | 0.68 |
| Han Lu | 5 | 0 | 0.34 |
| Chun Zhao | 6 | 27 | 7.67 |