William of Ockham (1285-1349)

William came from Ockham which is near Guildford, S.W. of London, just off junction 10 of the M25 with the A3. Medieval spelling was "rubbery" and while the village is now named 'Ockham', the spelling 'Occam' is frequently used in connection with W.

W is often credited with making a statement to the effect of, ''if two theories explain the facts equally well then the simpler theory is to be preferred'', but see below. This principle is widely known as 'Occam's Razor'.

All Saints Church, Ockham.

All Saints Church, Ockham, Surrey, contains a (recent) stained-glass window and statue of W.. The church dates from 13C. Behind the church is a gate into the private grounds of Ockham Park. The estate used to be owned by the Lovelace family, as in Ada Lovelace. The original house was destroyed by fire.

• Mach, Ernst. The Science of Mechanics: A Critical and Historical Account of Its Development, (Trans. T. J. McCormack (1960)) Open Court, La Salle IL., pp.577ff.
• Thorburn, W. M. Occam's Razor, Mind, 24, pp.287-288, 1915.
• Burns, C. Delisle. Occam's Razor, Mind, 24, pp.392, 1915.
• Thorburn, W. M. The Myth of Occam's Razor, Mind, 27(3), pp.345-353, 1918 [doi:10.1093/mind/XXVII.3.345].

The force of these articles is to emphasise that Ockham (a) is not recorded as having, and (b) wouldn't have, said 'Entia non sunt multiplicanda praeter necessitatem' (Don't multiply entities except by necessity). He did say 'Pluralitas non est ponenda sine necessitate' (plurality shouldn't be posited without necessity). Similar forms are found in the writings of his teacher Duns Scotus (c1266-1308)[1].

You can even get Aristotle in the Physics (book I, chapter vi) saying things like 'for the more limited, if adequate, is always preferable'. Or in (book VIII, chapter vi) 'for if the consequences are the same it is always better to assume the more limited antecedent'.

- marke.

[1] Duns Scotus, John: c1266-1308, from Encyclopaedia Britannica.

Minimum Message Length (MML) inference is a practical, automated method of machine learning along the razor's line.