October 23, 2017

The cybernetics of day-to-day behaviour

One cannot study a man eating a sandwich, without taking into account both the properties of the man and those of the sandwich. Similarly, one cannot regard a man apart from the environmental conditions to which his evolutionary development was but a long-term adaptive response.

The minimum unit of behavioural analysis must clearly be the biological system plus its environment which together must be regarded as constituting a larger system. The former must possess a control mechanism which must fulfil what are teleonomically two different functions: that of providing a hierarchical organisation of instructions transmitted from generation to generation and a mechanism for ensuring its adaptation to environmental changes. This can only be accomplished if associated with a model paralleling or representing the system to which adaptive responses must be mediated. In the field of genetics, protein synthesis, i.e., the process of ontogenetic growth, is today explained in terms of a control system of this sort. Thus Horowitz writes (1):

“It seems evident that the synthesis of an enzyme—a giant protein molecule consisting of hundreds of amino acid units arranged end to end in a specific and unique order—requires a model or set of instructions of some kind. These instructions must be automatically transmitted from generation to generation, and they must be constant yet capable of evolutionary change. The only known entity that could perform such a function is the gene. There are many reasons for believing that it transmits information by acting as a model or template.”

Kenneth Craik (2) was undoubtedly the first to provide a similar explanation for ordinary behaviour, i.e., that which is mediated by the nervous system. He viewed the nervous system “. . . as a calculating machine, capable of modelling or paralleling external events”, and he considered this to be “. . . the basic feature of thought and of explanation”.

The most important quality of the model is that it does not represent the environment but the system, i.e. the sub-system and its environment. Why this is so is clear from the consideration that if the model is to provide that information required to ensure the increased stability of the system in a given environment, it must represent both the former and the latter, since changes in either one or the other will result in different behavioural requirements. The model will therefore be of the system as a whole.

One of the consequences of adopting this model of behaviour, is that the notion of learning by trial and error becomes untenable.

If we put a rat in a maze, we know that it can be taught to find its way out. However, before hitting upon the correct route, it will have to make a series of unsuccessful trials. Now, if these trials were arranged to form a series, would it be possible to put order into this series, or must each trial be considered merely a random one? The trial-and-error theory appears to assume the latter hypothesis. However, strictly random behaviour does not occur in an ordered system made up of a system whether it be an organism, a society, or an ecosystem. These all display varying degrees of order, and hence of non-randomness. It has been shown that people are incapable of choosing a random series of numbers, even when they set out to do so purposefully. If this is true, it is even more unlikely that they will be capable of making a random series of moves. (3).

Where there is order, there must be instructions, and an organisation of information, i.e., a cybernism.

Looked at slightly differently, if a rat finds its way through a maze as a result of a series of trials, what will determine its first trial? If a hundred possible moves are open to it, why should it start off by making one rather than any other?

If the move in fact it makes is haphazard, why should not all the others be haphazard too? Is a rat behaving in a haphazard way when it chooses to eat a piece of cheese rather than an iron nail, or when it feeds its own family rather than that of some other rat? If not, which actions are to be considered haphazard and which are not? The answer is that the notion of non-directive, haphazard or trial-and-error learning is totally irreconcilable with our knowledge of behaviour. Instead, one must regard each action as based on what, in the light of a system’s model of the environment, constitutes the most probable hypothesis.

Let us look a little more closely into the mechanism involved. Supposing that the first move made by the rat, rather than lead it towards the opening, led it instead to a further cul-de-sac, the model responsible for this error would have to be modified. Thus, when the rat made its move, the situation would be interpreted in the light of a new model—one that had taken into account the failure of its predecessor to interpret correctly the short-term environmental situation in which the rat had found itself, and one furnishing it with an ever-more precise representation of the system for the purpose of finding its way out of the maze. In other words, each action could be regarded as a correction of an error; and if we regard these actions as forming a series, then the latter would be ‘damped’, in the sense that the errors would be progressively reduced, until the correct route was found. Its ability to do this must be the function of the development of the rat’s nervous system and in particular of the precision with which the model represents the system of which the animal is part.


1. Horowitz, Norman H., “The Gene”, in Scientific American, October 1956.

2. Craik, Kenneth, The Nature of Explanation, Cambridge University Press, 1952.

3. Ramsey, W. R., Broadhirst, Anne, The Non-Randomness of Attempts at Random Responses, The British Journal of Sociology, Autumn 1968.

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