Multi-agent deep reinforcement learning based real-time planning approach for responsive customized bus routes
References
Recommendations
Deep reinforcement learning for multi-agent interaction
Multi-agent systems research in the United KingdomThe development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel ...
Mediated Multi-Agent Reinforcement Learning
AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent SystemsThe majority of Multi-Agent Reinforcement Learning (MARL) literature equates the cooperation of self-interested agents in mixed environments to the problem of social welfare maximization, allowing agents to arbitrarily share rewards and private ...
Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems
Agents and Artificial IntelligenceAbstractUsing multi-agent reinforcement learning to find solutions to complex decision-making problems in shared environments has become standard practice in many scenarios. However, this is not the case in safety-critical scenarios, where the ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
Pergamon Press, Inc.
United States
Publication History
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0