A Deep Reinforcement Learning Approach to Configuration Sampling Problem

Computer Science

• Deep Reinforcement Learning 100%
• Sampling Problem 100%
• Identification 50%
• Software Product Line 50%
• Feature Interaction 50%
• Software Systems 50%
• Heuristics 50%
• Algorithms 50%

INIS

• learning 100%
• configuration 100%
• sampling 100%
• computer codes 40%
• reduction 20%
• size 20%
• exploration 10%
• benchmarks 10%
• testing 10%
• interactions 10%
• samplers 10%
• exploitation 10%
• cost 10%
• environment 10%
• algorithms 10%
• redundancy 10%