Multi-agent deep reinforcement learning based real-time planning approach for responsive customized bus routes.
Binglin WuXingquan ZuoGang ChenGuanqun AiXing WanPublished in: Comput. Ind. Eng. (2024)
Keyphrases
- reinforcement learning
- multi agent
- real time
- high speed
- single agent
- action selection
- robotic control
- multi agent planning
- state space
- planning problems
- cooperative
- reactive agents
- multiagent systems
- machine learning
- partially observable
- learning agents
- model free
- function approximation
- dynamic programming
- road network
- multi agent systems
- temporal difference
- reinforcement learning agents
- heuristic search
- complex domains
- intelligent agents
- route planning
- multi agent reinforcement learning
- function approximators
- traffic signal control
- learning algorithm
- control system
- stochastic domains
- state abstraction
- markov decision problems
- planning under uncertainty
- ai planning
- markov decision processes
- multiple agents
- motion planning