Computation by asynchronously updating cellular automata

Because of the unpredictability of the order of update, computing on ACA is usually done by simulating a timing mechanism to force all cells into synchronicity after which well-established synchronous methods of computation can be used.In this paper, we present a more effective method of computation based upon a 4-state two-dimensional ACA with von Neumann neighborhood that is based on the construction in the cellular space of delay-insensitive circuits, a special type of asynchronous circuits, whose operations are robust to arbitrary delays in operators or interconnection lines.There is always a question of how simple these models should be in order to adequately describe what is being modelled.The use of asynchronous models can allow an extra level of realism in the model.We show that this novel ACA model can be used to construct a universal Turing machine, which suffices to prove its computational universality.I have a collection of computational models that could be described as asynchronous cellular automata.Cellular automata, as with other multi-agent system models, usually treat time as discrete and state updates as occurring synchronously.

Harvey and Bossomaier (1997) pointed out that stochastic updating in random boolean networks results in the expression of point attractors only: there is no repeatable cyclic behaviour, although they introduced the concept of loose cyclic attractors.In contrast, an asynchronous cellular automaton is able to update individual cells independently, in such a way that the new state of a cell affects the calculation of states in neighbouring cells.Implementations of synchronous updating can be analysed in two phases.Often, models like cellular automata are used to help understanding of processes that work in real life.By building simplified models, new insights can be learned.

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