Editorial message: special track on applications of spatial simulation of discrete entities

• Authors: William A. Maniatty;Boleslaw K. Szymanski
• Venue: Proceedings of the 2002 ACM symposium on Applied computing
• Year: 2002

Many important phenomena result from localized interactions including: population dynamics and epidemics, cell and tissue modeling, mobile computing and wireless networks. Modeling these systems can reduce experimentation costs or enable non-destructive in silica experimentation.Simulation models can be classified depending on how they represent reality, in particular time, space and simulated entities (objects). The simplest to described are models based on ordinary differential equations, which are aspatial and they may have either single time step for all objects, making time synchronous, or different time steps for different entities, making time asynchronous. Simulation entities are also described by a set of read valued parameters, so they are treated as continuous. It is well known that spatially explicit models can exhibit qualitatively different results than their aspatial counterparts [5]. This makes the models based on partial differential equations very common and popular. In this track however, we focus on a different category of models. To make this difference clear, we start with the following categorization of all models based on how they treat the three orthogonal aspects of simulations: simulation objects (entities) and the world that they inhabit (time and space). The categorization is shown in Table 1.The field of numerical computing is well studied, with numerous forums for extensive work and publication of spatial models using continuous time and treating entities as continuous (e.g. diffusion models [3, 1] or finite element method approaches [6, 11]. Traditionally, techniques for spatial modeling of discrete systems have tended to be published in application specific forums. In forming this track, we hoped to provide a unique forum for researchers in this area to come together and discuss various applications and approaches to spatial modeling.