On CAST.FSM computation of hierarchical multi-layer networks of automata

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Abstract

CAST.FSM denotes a CAST tool which has been developed at the Institute of Systems Science at the University of Linz during the years 1986-1993. The first version of CAST.FSM was implemented in INTERLISP-D and LOOPS for the Siemens-Xerox workstation 5815 (Dandelion). CAST.FSM supports the application of the theory of finite state machines for hardware design tasks between the architecture level and the level of gate circuits. The application domain, to get practical experience for CAST.FSM, was the field of VLSI design of ASICS's where the theory of finite state machines can be applied to improve the testability of such circuits (design for testability) and to optimise the required silicon area of the circuit (floor planning). An overview of CAST as a whole and of CAST.FSM as a CAST tool is given in [11]. In our presentation we want to report on the re-engineering of CAST.FSM and on new types of applications of CAST.FSM which are currently under investigation. In this context we will distinguish between three different problems: 1. the implementation of CAST.FSM in ANSI Common Lisp and the design of a new user interface by Rudolf Mittelmann [5]. 2. the search for systemstheoretical concepts in modelling intelligent hierarchical systems based on the past work of Arthur Koestler [3] following the concepts presented by Franz Pichler in [10]. 3. the construction of hierarchical formal models (of multi-layer type) to study attributes which are assumed for SOHO-structures (SOHO = Self Organizing Hierarchical Order) of A. Koestler. The latter problem will deserve the main attention in our presentation. In the present paper we will build such a hierarchical model following the concepts of parallel decomposition of finite state machines (FSMs) and interpret it as a multi-layer type of model. © 2011 Springer-Verlag Berlin Heidelberg.

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Affenzeller, M., Pichler, F., & Mittelmann, R. (2001). On CAST.FSM computation of hierarchical multi-layer networks of automata. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2178 LNCS, pp. 36–44). Springer Verlag. https://doi.org/10.1007/3-540-45654-6_3

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