(untitled) (ENVIRONMENT. TECHNOLOGY. RESOURCES. Proceedings of the International Scientific and Practical Conference, 2006)
In the search for computational models that help to understand the dynamics of Complex Systems, one can take a great advantage from the impressive acceleration of computer tools and techniques. In fact the very structure of computation on digital computers has inspired the introduction of new class of models (algorithms), where interaction among degrees of freedom are expressed by logical rules acting over a discrete state space – something much closer to "biological language" than to standard (floating point) physical models. Starting from the definitions of spin systems, with little changes we reach a definition a new model that is well suited to describe different simulation systems. Such class of models is can be considered a subclass of the Agent-Based systems in vogue nowadays. Moreover, we shortly describe two microscopic simulators of this type, which are being used to study microscopic phenomena in two completely different fields of application, namely immunology and finance. As a final remark, given the lattice representation of space, such computational-modeling paradigm is well suited for efficient and "relatively simple" parallelization. Indeed, both models have been implemented to run on parallel computers adopting the Message Passing paradigm for Distributed Memory machines.