Evolvable Hardware is a combination of electronics and evolution. We have discussed the error of adhering too closely to the conventional principles of electronics, but there are also potential pitfalls in blindly applying ideas from natural evolution.
Consider biological neural networks. Compared to electronics, the neuron response and signal propagation times are extremely slow. On the other hand, there is very high connectivity in three dimensions, contrasting with the highly restricted planar wiring in VLSI. The two media -- biological cell based and silicon VLSI based -- provide very different resources. A structure evolved to exploit the former may not efficiently utilise the latter. It may be possible to evolve parallel distributed architectures better tailored to the opportunities provided by VLSI than models of biological neural networks are. Such an architecture might use the high speed of VLSI to compensate for limited connectivity in a more sophisticated way than the multiplexing schemes commonly seen in VLSI implementations of neural nets. Hence it would be unwise to rigidly limit EHW to a neuro-mimetic structure when intrinsic EHW can offer a more unconstrained exploitation of hardware resources. For engineering purposes, `VLSI-plausible' architectures are required, not `biologically-plausible' ones.
In the same way that the architecture of natural nervous systems evolved to be suited to the restrictions and opportunities of biology, so did the process of natural evolution itself adapt to the resources available (``the evolution of evolvability''). The large timescale, highly parallel, distributed co-evolution found in nature is somewhat different that possible in present-day implementations of artificial evolution. It is thus justifiable to use biologically-implausible mechanisms where these are effective, for example in the setting of the mutation rate or in the morphogenesis process. The aim is to arrive at an implementation of artificial evolution that is inspired by nature, but suited to the facilities available.
We have now proposed a synthesis of genetic algorithms, natural evolution and electronics that adapts each in the formation of a new field: Intrinsic Evolvable Hardware. The next section begins to put some of the ideas into practice.