Mengmeng Chen and Luis Rabelo
Optimization of makespan in scheduling is a highly desirable research topic, deadlock detection and prevention is one of the fundamental issues. Supported by what learned from this class, a reinforcement learning approach is developed to unravel this optimization difficulty. By evaluating this RL model on forty classical non-buffer benchmarks and compare with other alternative algorithms, we presented a near-optimal result.
この記事をシェアする
English 
Spanish 
Chinese 
Russian 
German 
French 
Portuguese 
Hindi 