Theoretical and Experimental Insights into Decentralized Combinatorial Auctions

Combinatorial Auctions (CAs) are promising to increase so-cial welfare by enabling bidders to express their valuationon any combination of items. A major issue of many CAsis the requirement to optimally solve the NP-hard Combi-natorial Allocation Problem. To release a centralized auc-tioneer from that computational burden he can shift it tothe bidders. One of the few discussed decentralized auc-tions is PAUSE, in which bidders suggest new allocations tothe auctioneer. In our theoretical analysis we examine thebidders\u27 bid complexity and determine a worst case boundconcerning eciency, if bidders follow a prot maximizingstrategy. Based on these results we conduct computationalexperiments with dierent bidding and computation strate-gies, and analyze their impact on eciency, auctioneer\u27s rev-enue and auction runtime. Surprisingly, even if agents de-viate from the optimal bid price calculation, PAUSE stillachieves high levels of eciency and auctioneer\u27s revenuecompared to the Combinatorial Clock auction