Price Auction

Price auctions, particularly in online advertising, are a central focus of research aiming to optimize bidding strategies for advertisers and revenue generation for platforms. Current research emphasizes the development of robust and efficient algorithms, such as reinforcement learning and gradient-based methods, to handle various auction formats (first-price, second-price, and hybrids), budget constraints, and strategic interactions between bidders. These advancements are crucial for improving the efficiency and fairness of online advertising markets, impacting both advertiser profitability and platform revenue. Furthermore, the study of transparency and information feedback in auctions is revealing how the design of these mechanisms significantly affects learning dynamics and overall market outcomes.