Periodic Reporting for period 4 - COMPECON (Complexity and Simplicity in Economic Mechanisms)
Berichtszeitraum: 2021-11-01 bis 2023-04-30
The aim of this proposal is to study the role and implications of such complexity and to start developing a coherent economic theory that can handle it. We aim to identify various measures of complexity that are crucial bottlenecks and study them. Examples of such complexities include the amount of access to data, the length of the description of a mechanism, its communication requirements, the cognitive complexity required from users, and, of course, the associated computational complexity. On one hand we will attempt finding ways of effectively dealing with complexity, when needed, and on the other hand, attempt avoiding complexity, when possible, replacing it with ``simple'' alternatives without incurring too large of a loss.
(*) Complexity of multi-item auctions where we understand to a large extent the trade-off between complexity and revenue, as well as the required "information gathering" complexity involved.
(*) The complexities of communication, information exchange, and preference elicitation in several complex scenarios such as fair cake cutting, local equilibria, and fixed-point computation.
(*) Dynamics in Growing Markets.
(*) The dynamics and induced incentives of learning agents that participate in repeated games and auctions for their users.
Beyond the many specific results obtained, an integrative "bigger picture" understanding emerged in three significant areas:
(*) Complexity of multi-item auctions: the trade-off between complexity and revenue
(*) Sample complexity needed for estimating value and bid distributions in auctions
(*) The role of communication in a multitude of complex market-like economic scenarios
New directions for research were opened regarding the dynamics and induced incentives of learning agents that participate in repeated games and auctions for their users.
Finally, our research that was motivated by economic scenarios has yielded back interesting questions in pure complexity.