Asfar Ahmad
Electrical engineering
Hometown: Chandler, Arizona, US
Graduation date: Fall 2027
FURI | Fall 2026, Needs Review
Computational Analysis of an Improved Reinforcement Learning Queueing Algorithm
Memory complexity is a major limiting factor when implementing reinforcement learning (RL) algorithms to service large queueing systems. This research reports the results of a new RL algorithm, with memory complexity 2N, where N is the number of queues in the system, which is a significant improvement on the previous minimum memory complexity found in the literature, UN, where U is the queue buffer size. Such a reduction could significantly lower the cost of running servers in data centers, thus potentially lowering the cost of commonly used internet services.
Mentor: Ahmed Ewaisha
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