Learning Agent Models in SeSAm (Demonstration)
Robert Junges, Franziska Klügl · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2013
Designing the agent model in a multiagent simulation is a challenging task due to the generative nature of such systems. In this contribution we present an extension to the multiagent simulation platform SeSAm, introducing a learning-based design strategy for building agent behavior models.