Improving modeling of other agents using stereotypes and compactification of observations

We investigate possible improvements to modeling other agents based on observed situation-action pairs and the nearest neighbor rule. Stereotype models allow for good predictions of a modeled agentýs behavior even after few observations. Periodic reevaluation of the chosen stereotype and the potential for switching between different stereotypes or to the observation based model aids in dealing with very similar (but not identical) stereotypes and agents that do not conform to any stereotype. Finally, compactification of observations keeps the application of the model efficient by reducing comparisons within the nearest neighbor rule, but sometimes at the cost of losing valuable information.