1998, with Tino Gramss, Stefan Bornholdt, Melanie Mitchell, Thomas Pellizzari*Non-Standard Computation*.*Travels to the Nanoworld*. 1999

- Molecular Computation. 1998. (In
)*Non-Standard Computation*

This promised to be a very interesting book, but it was let down for me
by being too low level -- too much about the scientific and technological
bases, and not enough about any new *computational paradigms*. (The
very poor level of proof reading, with some chapters thick with spelling
mistakes, also detracts.)

I was hoping for an overview of what new tools are being added to our computational capability, with maybe a review of the current state of the art, but what I got was a bunch of essays that have an idiosyncratic viewpoint, with all the details in the wrong places (for me, at least).

For example, the chapter on Genetic Algorithms devotes hardly any space
to the schemata model (beyond saying it is intuitive) but instead develops
a "statistical mechanics" model, without then providing the
intuition of how this model helps us to cast or solve new computational
problems. It also seems to imply that *mutation* is the key concept,
with *cross-over* just an interesting second order add-on (whereas
the study of genetic algorithms has shown is that cross-over is key, with
mutation playing a surprisingly small role).

The two chapters on quantum computing range over the theoretical QM
underpinnings, and the current technology, but again provide no intuition
of how these devices work *as computers*. (And the second of these
chapters has an almost useless bibliography, since it omits the papers'
titles.)

So I was left disappointed.

- • Heinz Georg Schuster.
**Introduction to Non-standard Computation**. 1998 - • Michael Gross.
**Molecular Computation**. 1998 - Using DNA to solve computational problems can allow massive
parallelism, by exploring 10
^{19}cases in parallel. This doesn't solve the trouble with exponentially difficult problems -- but it does delay it by several orders of magnitude! Currently, to program such a device, one needs to be a good bench chemist -- by DNA-sequencing technologies might make automatic compilation easier.

Supramolecules are large molecules that are (partly) built from*non*-covalent bonds. Natural supramolecules include DNA; artificial ones also look promising for computational applications. - • Stefan Bornholdt.
**Genetic Algorithms**. 1998 - Solving optimisation problems with artificial evolution
- • Melanie Mitchell.
**Computation in Cellular Automata: A Selected Review**. 1998 - A good overview of what cellular automata are, and a clear
description of how higher-level 'particles' can be used to design
cellular automata algorithms. [By far the best chapter. I find cellular
automata intrinsically interesting, but this chapter still left me
wondering what advantages they have
*as computers*.] - • Tino Gramss.
**The Theory of Quantum Computation: An Introduction**. 1998 - Theoretical quantum mechanic underpinnings of quantum computers -- all Hamiltonians and reversibility
- • Thomas Pellizzari.
**Quantum Computers: First Steps Towards a Realization**. 1998 - Current technology for building (very small!) quantum computers, including error correction