A Rule-Aware Structured Agent Architecture for Decision-Making in Heterogeneous Multi-Agent Traffic
Efficient and safe decision-making for autonomous vehicles in heterogeneous, multi-agent traffic environments remains a significant challenge. A key limitation of existing deep reinforcement learning (DRL) approaches is their reliance on monolithic ag
Authors
- Shidong Liang (ORCID: https://orcid.org/0000-0002-2191-6187)
- Minghui Ma (ORCID: https://orcid.org/0000-0002-7080-4376)
- Tao Wang (ORCID: https://orcid.org/0009-0003-1825-0163)
Publication Details
- Published
- 2025-09-19
- DOI
- https://doi.org/10.36227/techrxiv.174284875.58134352/v4
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00