ABSTRACT
Like Picasso’s, Vela’s prolific work has seen several ‘periods’, as browsing through this volume will have already revealed. In the ‘computable economics’ period, he has elegantly and convincingly argued that a reasonable1 benchmark for the rationality of the perfectly rational economic agent could be a Universal Turing Machine. I will not try to argue in favour of or against Vela’s perfect rationality, but I will be contented, as a ‘working hypothesis’, to assume that some Turing Machine ticks between his occipital and temporal bones. This note, an application of learning in the sense of inductive inference, was inspired by my mentor, friend and thesis co-director at UCLA (a.k.a. Kumaraswamy Velupillai) who, a few years back, suggested the topic of my dissertation: ‘computable’ learning in macroeconomics. If I were to attempt to identify (in a similar exercise) Kumaraswamy’s Turing Machine so as to determine a name for the function responsible for his output, I would suggest to start the induction experiment from a text composed of all the quotes he has chosen, over the years. This method of information presentation would serve at least two purposes. On the
one hand, it would show how Vela has superbly managed to introduce, exemplify, support and subliminally transmit the wealth of his ideas, his multifaceted results, his dynamic messages and consistently robust criticisms of inaccuracies and of approximate analysis. On the other hand, Velupillai’s evident pleasure with appropriate quotes from the classics reveals his indomitable commitment to learn, harness and ultimately master the Language (with a capital ‘L’). Not surprisingly, this second aspect clearly shows how hopeless the suggested exercise would be. It would amount to ask whether, in principle, the learner can learn itself . . Or, perhaps, it might be trivial to get the answer: I should simply ask Vela. In the matter of learning, memory has an eminent role and some of the results I will employ in this scribble2 have been generalized and expanded3 to introduce explicitly memory constraints in the learner. It appears that the sense of smell is the most powerful of the senses in recording and triggering the retrieval of precise memories – not very dissimilar from Proust’s Madeleine. Kumara Vela Swamypillai’s memory is recognized as nearly prodigious, but, I am told, is not photographic. However, it may be of the olfactory variety. In this case, it will have certainly helped in developing his unerring judgement on what is relevant and interesting if we accept Richard Goodwin’s position on the intellectual approach of the good researcher as reported by Robert Solow:
The unspoken message was that if a thing was worth doing it is worth doing playfully. Do not misunderstand me: ‘playful’ does not mean ‘frivolous’ or ‘unserious’. It means, rather, that one should follow a trail the way a puppy does, sniffing the ground, wagging one’s tail, and barking a lot, because it smells interesting and it would be fun to see where it goes.
