Taivo Lints Blog

An updated 2004 year version of the book originally published in 1986.

It's a 576 page book filled with practical information about "how to survive in the wild, in any climate, on land or at sea". Topics include: the will to live; survival kit; knives; acquiring water and food (including how to test unknown plants for edibility, and how to catch animals, birds, fish without proper equipment); car and plane accidents; survival strategies in polar regions, mountains, seashores, islands, arid regions and tropical regions; campcraft; navigation and weather signs; traveling on foot and on rafts; first aid and medical treatment; survival at sea; rescue operation basics (for the one being rescued, not for the one conducting the operation); strategies for surviving in natural and man-made disasters.

Highly recommended for everybody, especially for travelers.

More info at Amazon: http://www.amazon.com/dp/0060578793/

A book by Ricard V. Solé and Brian C. Goodwin, originally from year 2000.

The cover gives an impression that the book is a discussion about what life is, but this is not the case. Instead, it is a good and relatively easy to read overview of a large number of tools and approaches that are often referred to as complexity science. There are deterministic chaos, emergence, criticality, self-organization, patterns in excitable media, entropy, Ising model, information theory, renormalization, self-similarity, sand-pile model, metabolic networks, genetic networks, cell differentiation, reaction-diffusion systems, biological clocks, neural nets, phase transitions, ant colonies, nest building in social insects, biodiversity, ecological stability, viral quasispecies, catalytic chemical networks, evolution and extinction, stock market fluctuations, urban growth, traffic models, etc.

As the page count is around 300, the book obviously doesn't go into great details of every concept, neither does it always have all terminology explained, neither is there a coherent overarching story. Thus I don't know if it would be a good reading for somebody who has never heard most of the presented ideas before, but for me it is a good collection of notes that can be used for sparking inspiration and for quickly remembering the key concepts, the details of which should then be looked up from other sources. So, in general I like it.

More information at Amazon: http://www.amazon.com/dp/0465019285/

and if you have access to Wiley InterScience, then: http://www3.interscience.wiley.com/cgi-bin/abstract/97519452/

A book from 2006, with a slightly misleading title. Actually it is only about Particle Swarm Optimization and Ant Colony Optimization, plus introduction to optimization and Evolutionary Computation in the first parts of the book. But as of PSO and ACO, it is a very clearly written and thorough review work -- there are 667 references.

The few more general sections occasionally seemed to me somewhat less substantial. For example the comparison of Particle Swarm Optimization vs. Evolutionary Computation quite strongly tries to separate them, while for me it seems that although it is very practical to have these different approaches, many of their underlying principles are overlapping quite heavily, if suitably interpreted (e.g. the trajectory of an individual in PSO should be compared to a trajectory of a generational family chain of parent-child successions in EC, and an explicit test should be done about whether such rules of EC could be found so that the trajectories would be similar to PSO, or vice versa. I haven't checked it, but at least reading the book didn't convince me that the check would fail.).

I would recommend the book to people who are seriously interested in Particle Swarm Optimization or Ant Colony Optimization. Those having a more general interest in swarm intelligence might find the book a bit limited in breadth, but flipping through it might be useful nevertheless.

More info at book's homepage: http://si.cs.up.ac.za/

A book originally from 1975, reprinted in 1992 with an additional chapter.

The work proposes a formal framework for studying adaptivity, and shows how the genetic processes can be generalized to be useful in many different disciplines (the 1975 book is the one that reportedly brought genetic algorithms into wider use). The approach indeed seems to be not presenting genetic evolution as just an example of an adaptive process, but as a (or The) source of inspiration and ideas for understanding all kinds of adaptive systems.

A very short summary of the formal framework:

An adaptive system could be specified by a set of objects (A, Omega, I, tau), where:

• A is the set of attainable structures (the domain of action of the adaptive plan).
• Omega is the set of operators for modifying structures.
• I is the set of possible inputs to the system from the environment.
• tau is the adaptive plan which, on the basis of the input and structure at time t, determines what operator is to be applied at time t.

A problem in adaptation would be said to be well posed once the following constructs have been specified:

• A set of plans, given either explicitly or implicitly, which are candidates for comparison.
• A set of possible environments (or states of the environment) that the system may encounter.
• A criterion for comparing the efficiency of different plans (under the uncertainty represented by the set of possible environments).

Reading the book was quite useful for me, as I am trying to understand the concept of adaptivity. But if your goal is to understand genetic algorithms, I'm sure you can find more up to date and easier to follow sources for that.

More information about the book at MIT Press: http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=7593

and at Amazon: http://www.amazon.com/dp/0262581116