  Turing presented a general representation scheme by which to achieve
artificial intelligence - unorganised machines. Significantly, these were a
form of discrete dynamical system and yet such representations remain
relatively unexplored. Further, at the same time as also suggesting that
natural evolution may provide inspiration for search mechanisms to design
machines, he noted that mechanisms inspired by the social aspects of learning
may prove useful. This paper presents initial results from consideration of
using Turing's dynamical representation within an unconventional substrate -
networks of Belousov-Zhabotinsky vesicles - designed by an imitation-based,
i.e., cultural, approach. Turing's representation scheme is also extended to
include a fuller set of Boolean functions at the nodes of the recurrent
networks.
