Solving the continuous time multiagent patrol problem

This paper compares two algorithms to solve a multiagent patrol problem with uncertain durations. The first algorithm is reactive and allows adaptive and robust behavior, while the second one uses planning to maximize longterm information retrieval. Experiments suggest that on the considered instances, using a reactive and local coordination algorithm performs almost as well as planning for long-term, while using much less computation time.

Authors

• Jean-Samuel Marier
• Camille Besse
• Brahim Chaib-draa

Keywords

• Unmanned aerial vehicles
• Robustness
• Information retrieval
• Monitoring
• Random variables
• Robotics and automation
• USA Councils
• Surveillance
• Path planning
• Learning
• Robust Behavior
• Upper Bound
• Value Function
• State Space
• Point-like
• Root Node
• Nodes In The Graph
• Number Of Agents
• Low Computational Cost
• Markov Decision Process
• Tree Search
• Position Of Agent
• Online Algorithm
• Policy Agencies
• Vertex Position
• Unit Square
• Augmented State
• Travel Duration
• Experimental Class
• Joint Policy
• Policy Value
• Decision-making Process
• Edge Length
• Multiagent
• UAV
• Online
• Patrol