Abstract
Modelling and simulation of robotic control systems allows for low cost analysis and experimentation. However, creating these models requires a level of technical expertise. To improve the technical quality of such models, we propose a case-based reasoning approach to learn the behaviour of models using the DEVS formalism. By observing a desired behaviour, in the form of outputs produced in response to inputs, a DEVS model of the behaviour can be built. This model can then be used during simulation to imitate the behaviour of interest. Our results show that this learning approach can be used to successfully imitate the behaviour of several DEVS models. Additionally, it can be used to transfer behaviour to and from a non-DEVS model.
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