author : Tino Gramss

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.

Contents

• Heinz Georg Schuster.

Introduction to Non-standard Computation

• Michael Gross.

Molecular Computation

Using DNA to solve computational problems can allow massive parallelism, by exploring 10¹⁹ 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

Solving optimisation problems with artificial evolution

• Melanie Mitchell.

Computation in Cellular Automata: A Selected Review

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

Theoretical quantum mechanic underpinnings of quantum computers -- all Hamiltonians and reversibility

• Thomas Pellizzari.

Quantum Computers: First Steps Towards a Realization

Current technology for building (very small!) quantum computers, including error correction