"Reinforcement learning based monotonic policy for online resource allo" by Pankaj Mishra and Ahmed Moustafa
This research aims to design an optimal and strategyproof mechanism for online resource allocation problems. In such problems, consumers randomly arrive with their resource requests in an arbitrary manner. As a result, there is uncertainty in the future resource demands. In addition, the allocation and payment decisions depend on the providers’ past experiences. To address these challenges, we propose a novel reinforcement learning algorithm for optimising the resource allocation policy. The proposed algorithm adopts a novel monotonic reward shaping function that uses a dominant-resource mul...
Source: uow.edu.au