Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
In an attempt to cope with time-varying workload, traditional adaptive Time Warp protocols are designed to react in response to performance changes by altering control parameter c...
In this paper we present an advanced bidding agent that participates in first-price sealed bid auctions to allocate advertising space on BluScreen – an experimental public adve...
Alex Rogers, Esther David, Terry R. Payne, Nichola...
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...