We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
Classic direct mechanisms require full type (or utility) revelation from participating agents, something that can be very difficult in practical multi-attribute settings. In this...
Abstract The advent of large-scale distributed systems poses unique engineering challenges. In open systems such as the internet it is not possible to prescribe the behaviour of al...
Initial results of an experiment devised to combine Bond-Graph modeling and simulation with genetic programming for automated design of a simple mechatronic system are reported in...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...