Co-evolutionary Agents in Combinatorial Sealed-bid Auctions for Spectrum Licenses Markets

Allocating scarce resources is a difficult duty governments must face. Furthermore, when participants exhibit complex preference structures (substitutes and complements) this task is even trickier. Combinatorial auctions are a good alternative for solving this problem. In this work we have developed a simulator of a combinatorial first-price sealed-bid auction. The bidding behaviour has been simulated by the application of co-evolutionary dynamics in an agent-based model. This model assumes independent bidders with bounded rationality trying to maximize profits. Finally, the simulations have been tested for two environments that involve the sale of spectrum licenses (

digital dividend

). These techniques are a helpful tool to support governments taking decisions in the awarding process.