We study the recognized open problem of designing revenuemaximizing combinatorial auctions. It is unsolved even for two bidders and two items for sale. Rather than pursuing the pu...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
Abstract— This paper presents a genetic algorithmic approach for finding efficient paths in directed graphs when optimizing multiple objectives. Its aim is to provide solutions...
We continue the recent line of work on the connection between semidefinite programming-based approximation algorithms and the Unique Games Conjecture. Given any boolean 2-CSP (or...
In this paper we present a system that facilitates virtual museum development and usage. The system is based on a game engine, ensuring thus minimal cost and good performance, and...
Victor Mateevitsi, Michael Sfakianos, George Lepou...