AAAI 2025 Workshop MALTA Submissions

Addressing the MARL Scalability Problem in Autonomous Transport using Practical Mean-Field Games
Patrick Benjamin, Alessandro Abate
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone
Dynamic Shortest Path Planning with Lookahead Traffic Information
Joon Moon, Qadeer Ahmed
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 LightningTalk
- Readers: Everyone
Multi-Agent Decision S4: Leveraging State Space Models for Offline Multi-Agent Reinforcement Learning
Ashmita Bhattacharya, Malyaban Bal
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 LightningTalk
- Readers: Everyone
Fairness in Traffic Control: Decentralized Multi-agent Reinforcement Learning with Generalized Gini Welfare Functions
Umer Siddique, Peilang Li, Yongcan Cao
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone
A Constrained Multi-Agent Reinforcement Learning Approach to Traffic Management
Anirudh Satheesh, Keenan Powell
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone
A Decentralized Approach to Autonomous Train Platooning
Benat Froemming-Aldanondo, Maria Gini
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 LightningTalk
- Readers: Everyone
Cooperative Cruising: Reinforcement Learning based Time-Headway Control for Increased Traffic Efficiency
Yaron Veksler, Sharon Hornstein, Han Wang, Maria Laura Delle Monache, Daniel Urieli
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone
TransferLight: Zero-Shot Traffic Signal Control on any Road-Network
Johann Schmidt, Frank Dreyer, Sayed Abid Hashimi, Sebastian Stober
- Published: 10 Dec 2024, Last Modified: 11 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone
TACTIC: Task-Agnostic Contrastive pre-Training for Inter-Agent Communication
Peihong Yu, Manav Mishra, Syed Zaidi, Pratap Tokekar
- Published: 10 Dec 2024, Last Modified: 14 Feb 2025
- MALTA 2025 Talk
- Readers: Everyone