Junges, RobertKlügl, Franziska2018-01-082018-01-0820132013https://dl.gi.de/handle/20.500.12116/11361In this project report, we describe ongoing research on supporting the development of agent-based simulation models. The vision is that the agents themselves should learn their (individual) behavior model, instead of letting a human modeler test which of the many possible agent-level behaviors leads to the correct macro-level observations. To that aim, we integrate a suite of agent learning tools into SeSAm, a fully visual platform for agent-based simulation models. This integration is the focus of this contribution.Agent learningAgent modelingAgent-based simulationText/Journal Article1610-1987