MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments.
Zuxin LiuBaiming ChenHongyi ZhouGuru KoushikMartial HebertDing ZhaoPublished in: CoRR (2020)
Keyphrases
- dynamic environments
- path planning
- reinforcement learning
- multi agent
- reinforcement learning agents
- mobile robot
- single agent
- path planning algorithm
- collision avoidance
- autonomous agents
- obstacle avoidance
- potential field
- reinforcement learning algorithms
- multiple robots
- autonomous navigation
- optimal path
- path finding
- multi agent environments
- genetic algorithm
- dynamic and uncertain environments
- multi agent systems
- degrees of freedom
- path planner
- motion planning
- agent systems
- autonomous vehicles
- state space
- real environment
- multiagent systems
- intelligent agents
- multiple agents
- robot path planning
- multi robot
- simultaneous localization and mapping
- optimal policy
- trajectory planning
- autonomous systems
- unmanned aerial vehicles
- changing environment
- indoor environments
- unknown environments
- markov decision processes
- search space
- real robot
- software agents
- aerial vehicles
- learning algorithm