Minimizing convergence error in multi-agent systems via leader selection: A supermodular optimization approach

Keyphrases

• Continuous Relaxation 16%
• Control Input 16%
• Convergence Error 100%
• Convex Hull 16%
• Desired State 16%
• Discrete Optimization Algorithm 16%
• Distribution Network 16%
• Dynamic Networks 33%
• Fast Discrete Optimization 16%
• Graph Network 16%
• Intermediate State 16%
• Leader Selection 100%
• Leader-follower System 16%
• Minimum Size 16%
• Multi-agent Systems 100%
• Network Dynamics 16%
• Optimization Approach 100%
• Optimization Framework 16%
• Performance Guarantee 16%
• Random Walk 16%
• Selection Problem 16%
• Selection Strategy 16%
• Static Networks 16%
• Submodularity 16%
• Supermodular 16%
• Supermodular Optimization 100%

Computer Science

• Discrete Optimization 50%
• Distribution Network 50%
• Dynamic Network 100%
• Intermediate State 50%
• Multi Agent Systems 100%
• Network Dynamic 50%
• Optimization Algorithm 50%
• Optimization Framework 50%
• Performance Guarantee 50%
• Problem Selection 50%
• Random Walk 50%
• Selection Method 50%

Mathematics

• Approximates 16%
• Convergence Error 100%
• Convex Hull 16%
• Fixed Number 16%
• Intermediate State 16%
• Lower Convergence 16%
• Minimizes 33%
• Network Dynamic 16%
• Numerical Analysis 16%
• Prior State 16%
• Random Walk 16%
• Set Size 16%