d at a high abstraction level, and consists in an expectation-driven search starting from symbolic object descriptions and using a version of a distributed blackboard system for re...
Gian Luca Foresti, Vittorio Murino, Carlo S. Regaz...
A major research challenge in multi-agent systems is the problem of partitioning a set of agents into mutually disjoint coalitions, such that the overall performance of the system...
Tomasz P. Michalak, Jacek Sroka, Talal Rahwan, Mic...
We consider the problem of coordinating a team of agents engaged in executing a set of inter-dependent, geographically dispersed tasks in an oversubscribed and uncertain environme...
Laura Barbulescu, Zachary B. Rubinstein, Stephen F...
In the strategyproof classification setting, a set of labeled examples is partitioned among multiple agents. Given the reported labels, an optimal classification mechanism returns...
Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosens...
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...