72
6
The Nature of Information
environment. In simpler terms, this may be quantified as value in terms of a change
in behaviour (assuming that enough data on replicate systems or past events are
available to enable the course of action that would have taken place in the absence
of the received information to be determined).
Information is inherently discrete (quantal) and thus based on combinatorics,
which also happens to suit the spirit of the digital computer. In biology, if “geno-
type” constitutes the signs, then “phenotype” constitutes meaning. Action is self-
explanatory and linked to adaptation (see Sect. 3.4). Biological function might be
considered to be the potential for action.
Table 6.1 provides a further summary of some of the concepts discussed in this
chapter.
References
Ashby WR (1956) An introduction to cybernetics. Chapman and Hall, London
Ashby WR (1962) Principles of the self-organizing system. In: von Foerster H, Zopf GW (eds)
Principles of self-organization. Pergamon Press, Oxford, pp 255–278
Bennett CH (1988) Logical depth and physical complexity. In: Herken R (ed) The universal Turing
machine–a half century survey. University Press, Oxford, pp 227–257
Bernoulli D (1738) Specimen theoriae novae de mensura sortis. Commentarii Academiae Scien-
tiarum Imperialis Petropolitanae 5:175–192
Bernoulli D (1777) Diiudicatio maxime probabilis plurium observationem discrepantium atque
verisimillima inductio inde formanda. Acta Acad Sci Imp Petrop 1:3–23
Carnap R, Bar-Hillel Y (1952) An outline of a theory of semantic information. MIT Research
Laboratory of Electronics Technical Report No 247
Chernavsky DS (1990) Synergetics and information. Matematika Kibernetika 5:3–42 (in Russian)
Dewey TG (1996) Algorithmic complexity of a protein. Phys Rev E 54:R39–R41
Dewey TG (1997) Algorithmic complexity and thermodynamics of sequence-structure relationships
in proteins. Phys Rev E 56:4545–4552
Euler L (1777) Observationes in praecedentem dissertationem illustris Bernoulli. Acta Acad Sci
Imp Petrop 1:24–33
Fisher RA (1951) The design of experiments, 6th edn. Oliver and Boyd, Edinburgh
von Foerster H (1960) On self-organizing systems and their environments. In: Yorvitz MC, Cameron
S (eds) Self-organizing systems. Pergamon Press, Oxford
Good IJ (1969) Statistics of language. In: Meetham AR (ed) Encyclopaedia of linguistics, informa-
tion and control. Pergamon Press, Oxford, pp 567–581
Karbowski J (2000) Fisher information and temporal correlations for spiking neurons with stochastic
dynamics. Phys Rev E 61:4235–4252
Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Statist 22:79–86
Mackay DM (1950) Quantal aspects of scientific information. Phil Mag (ser 7) 41:289–311
Markov AA (1913) Statistical analysis of the text of “Eugene Onegin” illustrating the connexion
with investigations into chains. Izv Imp Akad Nauk (ser 6) no 3:153–162 (in Russian)
Nowak MA, Plotkin JB, Jansen VAA (2000) The evolution of syntactic communication. Nature
404:495–498
Ramsden JJ (2001) Computational aspects of consciousness. Psyche Problems Perspect 1:93–100
Ramsden JJ (2010) Less is different. Nanotechnol Percept 6:57–60
Shannon CE (1951) Prediction and entropy of printed English. Bell Syst Tech J 30:50–64