Successful interaction between autonomous agents is contingent on those agents making decisions consistent with the expectations of their peers -- these expectations are based on ...
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 describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Abstract. Human users trying to plan and accomplish informationdependent goals in highly dynamic environments with prevalent uncertainty must consult various types of information s...
In this study, we describe our system at the Intellectual Property track of the 2009 CrossLanguage Evaluation Forum campaign (CLEF-IP). The CLEF-IP track addressed prior art searc...