In this paper, we present a genetic algorithmic approach to automated auction mechanism design in the context of \cat games. This is a follow-up to one piece of our prior work in the domain, the reinforcement learning-based grey-box approach. Our experiments show that given the same search space the grey-box approach is able to produce better auction mechanisms than the genetic algorithmic approach. The comparison can also shed light on the design and evaluation of similar search solutions to other domain problems.
Niu, Jinzhong and Parsons, Simon, "A Genetic Algorithmic Approach to Automated Auction Mechanism Design" (2016). CUNY Academic Works.