An Object-Oriented Framework for the Simulation of Neural Nets

The field of software simulators for neural networks has been ex-panding very rapidly in the last years but their importance is still being underestimated. They must provide increasing levels of as-sistance for the design, simulation and analysis of neural networks. With our object-oriented framework (SESAME) we intend to show that very high degrees of transparency, manageability and flexibil-ity for complex experiments can be obtained. SESAME's basic de-sign philosophy is inspired by the natural way in which researchers explain their computational models. Experiments are performed with networks of building blocks, which can be extended very eas-ily. Mechanisms have been integrated to facilitate the construction and analysis of very complex architectures. Among these mech-anisms are t.he automatic configuration of building blocks for an experiment and multiple inheritance at run-time.