Cellular Automata Grid Research Articles

Grid anisotropy reduction for simulation of growth processes with cellular automaton

Growth processes simulated on a regular cellular automaton grid with simple capture rules are considerably influenced by the structure of the grid. Some of the growth directions are favored over others leading to highly anisotropic or, at least, orientation-dependent growth pattern. A new method is proposed for significant reduction of artificial grid anisotropy in 2D and 3D cellular automata with continuous state variable. The method employs additional diffusion process controlling the growth rate and allows for isotropic or anisotropic growth where the anisotropy is decoupled from the grid structure. Verification of the method is provided in the case of isotropic circular growth, isotropic growth of various shapes in uniform and spatially varying fields, and anisotropic growth with respect to orientation and symmetry of the pattern. Finally, the reduction of grid anisotropy is demonstrated in 2D simulation of dendritic grain growth in pure metal. The shape of the grain is shown to be virtually independent of the orientation. An example growth of a grain with six-fold symmetry is also included.

Towards a multi-agent model for visualizing simulated user behavior to support the assessment of design performance

We introduce the outline of a multi-agent model that can be used for visualizing simulated user behavior to support the assessment of design performance. We will consider various performance indicators of building environments, which are related to user reaction to design decisions. This system may serve as a media tool in the design process for a better understanding of what the design will look like, especially for those cases where design or planning decisions will affect the behavior of individuals. The system is based on cellular automata and multi-agent simulation technology. The system simulates how agents move around in a particular 3D (or 2D) environment, in which space is represented as a lattice of cells. Agents represent objects or people with their own behavior, moving over the network. Each agent will be located in a simulated space, based on the cellular automata grid. Each iteration of the simulation is based on a parallel update of the agents conforming local rules. Agents positioned within an environment will need sensors to perceive their local neighborhood and some means with which to affect the environment. In this way, autonomous individuals and the interaction between them can be simulated by the system. As a result, designers can use the system to assess the likely consequences of their design decisions on user behavior. We think that the system provides a potentially valuable tool to support design and decision-making processes, related to user behavior in architecture and urban planning.

Implantation of cellular automata

We consider a problem of grafting a fragment of one cellular automaton grid (implant) into the cavity cut out inside the grid of another cellular automaton (acceptor). The (non)deterministic and (a)synchronous cellular automata are examined. We offer two criteria for implantability when both implant and acceptor are passive and construct a hierarchy of implantability. Moreover, we show algorithms for active implantation (when an implant studies an acceptor actively) and compute bounds for the complexity of them.