A. Linden, Th. Sudbrak, Ch. Tietz, F. Weber
The field of software simulators for neural networks has been ex(cid:173) panding very rapidly in the last years but their importance is still being underestimated. They must provide increasing levels of as(cid:173) 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(cid:173) ity for complex experiments can be obtained. SESAME's basic de(cid:173) 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(cid:173) ily. Mechanisms have been integrated to facilitate the construction and analysis of very complex architectures. Among these mech(cid:173) anisms are t.he automatic configuration of building blocks for an experiment and multiple inheritance at run-time.