Books

Papers/Articles

Books : reviews

[cover]

Melanie Mitchell. Analogy-Making as Perception: a computer model. MIT Press. 1993

Rating: 3.5
[ unmissable | great stuff | worth reading | passes the time | waste of time | unfinishable ]

An in-depth description of Copycat, one of the projects at Douglas Hofstadter's Fluid Analogies Research Group

[cover]

Melanie Mitchell. An Introduction to Genetic Algorithms. MIT Press. 1996

 

[cover]

Tino Gramss, Stefan Bornholdt, Michael Gross, Melanie Mitchell, Thomas Pellizzari, editors. Non-Standard Computation: molecular computation, cellular automata, evolutionary algorithms, quantum computers. Wiley-VCH. 1998

Rating: 4.5
[ unmissable | great stuff | worth reading | passes the time | waste of time | unfinishable ]

reviewed 2 June 1999

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

[cover]

Lashon B. Booker, Stephanie Forrest, Melanie Mitchell, Rick L. Riolo, editors. Perspectives on Adaptation in Natural and Artificial Systems. OUP. 2005

 

Contents

Kenneth De Jong.
Genetic Algorithms: A 30 Year Perspective
John R. Koza.
Human-Competitive Machine Intelligence by Means of Genetic Algorithms
David E. Goldberg.
John Holland, Facetwise models, and Economy of Thought
Arthur W. Burks.
An Early Graduate Program in Computers and Communications
Oliver G. Selfridge.
Had We But World Enough and Time
Bernard P. Zeigler.
Discrete Event Abstraction: An Emerging Paradigm for Modeling Complex Adaptive Systems
Herbert A. Simon.
Good Old-Fashioned AI and Genetic Algorithms: An Exercise in Translation Scholarship
Douglas R. Hofstadter.
Moore's Law, Artificial Evolution, and the Fate of Humanity
Julian Adams.
Evolution of Complexity in Microbial Populations
Bobbi S. Low, Doug Finkbeiner, Carl Simon.
Favored Places in the Selfish Herd: Trading Off Food and Security
Rick L. Riolo, Robert Axelrod, Michael D. Cohen.
Tags, Interaction Patterns and the Evolution of Cooperation
Robert G. Reynolds, Salah Saleem.
The Impact of Environmental Dynamics on Cultural Emergence
Kenneth J. Arrow.
John Holland and the Evolution of Economics
W. Brian Arthur.
Cognition: The Black Box of Economics

[cover]

Melanie Mitchell. Complexity: a guided tour. OUP. 2009