Experimental demonstration of multi-agent learning and planning under uncertainty for persistent missions with automated battery management

Keyphrases

• Planning Problem 100%
• Experimental Demonstration 100%
• Battery Management 100%
• Multi-agent Planning 100%
• Multi-agent 100%
• Learning under Uncertainty 100%
• Cooperative Planning 100%
• Multi-agent Learning 100%
• Online Planning 100%
• Correlated Uncertainty 100%
• Planning Algorithms 100%
• Planning under Uncertainty 100%
• UAV 50%
• Parameter Estimation 50%
• State Dependence 50%
• Model Uncertainty 50%
• Planning Framework 50%
• Planners 50%
• Online Learning 50%
• Learning Framework 50%
• Individual Vehicle 50%
• Incremental Feature 50%
• Battery Swapping 50%
• Recharging Systems 50%
• Multi-Agent Markov Decision Processes 50%
• Feature Discovery 50%
• Fast Learning Algorithm 50%
• Health Dynamics 50%
• Integrated Learning 50%
• PRESENT Algorithm 50%
• Effcient 50%
• Decentralized Multi-Agent 50%
• Learning Plans 50%

Computer Science

• multi agent 100%
• multiagent learning 100%
• Planning Algorithm 66%
• Markov Decision Process 33%
• Learning Algorithm 33%
• Model Uncertainty 33%
• Electronic Learning 33%
• Unmanned Aerial Vehicle 33%

Engineering

• Cooperative 100%
• Unmanned Aerial Vehicle 50%
• Test Result 50%
• Model Uncertainty 50%
• Learning Algorithm 50%
• Decentralized Multi 50%
• Markov Decision Process 50%