Representing time and space

In earlier chapters we have not considered how apparently simple choices about how to represent time (synchronously, asynchronously, or event-based?) and space (as a grid, as a network, as points, as polygons?) may affect both model outcomes and also affect the realism of the resulting models. In this chapter various aspects of these choices are given due consideration.

6.1 Game of life with different update timings

This model demonstrates how changing the sequencing of the game of life update rule leads to different outcomes.

6.2 Majority rule automata under different update sequencing

This model demonstrates how changing the sequencing of the majority rule cellular automaton update rule leads to different outcomes.

6.3 Implementing an event queue

This model demonstrates how an event-based model of time can lead to much faster operation of functionally identical models.

6.4 Voter model on a hexagonal lattice

This model demonstrates a voter model on a hexagonal lattice. The outcomes are not qualitatively different from those on a grid-based lattice.

6.5 Voronoi tessellation based voter model

This model demonstrates a voter model on a Voronoi tessellation. Again, the outcomes are not qualitatively different from those on a grid-based lattice.

6.6 Game of life on an ‘infinite’ lattice

This model demonstrates how the game of life can be implemented on an ‘infinitely extensible’ lattice by only recording the locations of live cells.