Abstract. There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subje...
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Motivated by the problem of customer wallet estimation, we propose a new setting for multi-view regression, where we learn a completely unobserved target (in our case, customer wa...
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens ...
This paper describes our work constructing a generalized framework for modeling multi agent interactions in education-related applications. Historically, interactive learning syst...