And now also Stephen Toulmin has died … See this in memoriam and this one.) In 2009 we have lost two groundbreaking thinkers about defeasible argumentation (see the post on John Pollock).
His 1958 argument model has influenced many AI researchers (and others) although often indirectly (see e.g. this text). For me his much more recent Return to reason was also very stimulating.
Wigmore’s 1000+ pages work on the principles of judicial proof (including his charting method) is publicly available online: The principles of judicial proof as given by logic, psychology, and general experience, and illustrated in judicial trials. This is the 1913 version, not the second edition from 1931.
Two excerpts:
John Pollock, a founding father of the area of defeasible argumentation, has died. He combined theoretical, computational and practical considerations in his design of an ‘artificial person’, OSCAR (see, e.g., his Cognitive carpentry). In this high ambition, he has had no followers.
See, e.g., his influential paper Defeasible reasoning (in Cognitive Science, 11:481–518, 1987; also available in full text). A – too brief – one page introduction to his influential ideas on undercutting and rebutting defeaters is in this text (p. 229) on that other founding father of defeasible argumentation Stephen Toulmin.
I came across Marvin Minsky’s 2006 book _The Emotion Machine_ (draft available at his site). I briefly looked at what he had to say about commensense, the biggest hurdle for AI. Here is how he estimates how much a typical person knows, ‘a few dozen millions of items of knowledge’:
Everyone knows a good deal about many objects, topics, words, and ideas—and one might suppose that a typical person knows an enormous amount. However, the following argument seems to suggest that the total extent of a person’s commonsense knowledge might not be so vast. Of course, it is hard to measure this, but we can start by observing that every person knows thousands of words, and that each of those must be linked in our minds to as many as a thousand other such items. Also a typical person knows hundreds of uses and properties of thousands of different common objects. Similarly, in the social realm, one may know thousands of things about tens of people, hundreds of things about hundreds of people, and tens of useful items about as many as a thousand people.
This suggests that in each important realm, one might know perhaps a million things. But while it is easy to think of a dozen such realms, it is hard to think of a hundred of them. This suggests that a machine that does humanlike reasoning might only need a few dozen millions of items of knowledge.
I found it worthwhile to read a bit in this work by one of the big defenders of ‘knowledge-intensive AI’; the old-fashioned kind that I am a child of. (I only recently learnt that the pun GOFAI for good old-fashioned AI should probably be pronounced with ‘o’ as in ‘goof’.) I saw that (in the same chapter on commonsense) Minsky briefly comments on the currently fashionable ideas that we need to copy the brain and that we need to harvest the web.
Here are some points in a review by the neurologist Richard Restak that make me curious:
Actually, the loss of cells results from passive disuse — use it or lose it — rather than active deletion.
Of the 1.1 trillion cells in the human brain, only 100 billion are neurons.
[A]natomical interaction of neurons highlights only one aspect of brain functioning. Equally important are alterations of the brain’s chemical messengers, the neurotransmitters, along with changes in local and distributed electrical fields.
I looked at Minsky’s web site after I Wolfram|Alpha’ed him together with Norbert Wiener, about whom Lambert spoke to me yesterday. (Beware: Wolfram|Alpha is the latest geek tool; innovative, useful, addictive.)
In AI, prediction is associated with people such as Norbert Wiener (who “worked with McCulloch and Pitts and influenced a number of young researchers including Marvin Minsky”, Russel & Norvig 2003, 757). In law, prediction is associated with Oliver Wendell Holmes’ stance towards law: the law should be regarded as a prediction of what brings punishment or other consequences from a court (see Wikipedia; see there how Hart took a different view).
Pieter de Bie is currently in Edinburgh (with Simon Kirby and Thom Scott-Phillips) working on a game in which players must learn to communicate with little grounding. In a recent discussion about the progress of his work I was reminded of one of Léon Vié’s elegant puzzles that appeared in the 1980s in the NRC Handelsblad: a message from space. It is in Dutch, but here is all you need to know to do the puzzle: what is the meaning of the 14th group of signs received by Ipokrypa, an inhabitant of the planet Jupiter, and where does the message come from? If you really need the solution, it is posted at http://bartver.files.wordpress.com/2009/04/vie
.pdf.
Something to think about every now and then (for me at least):
The peer review process is a form of pure procedural justice (Rawls): there is no criterion for the fairness of its outcome other than the correct application of the procedure itself.
This perspective is enlightening (and sobering) both when receiving a review’s outcome (pos or neg) and when writing a review.
I came across a message that I sent to Ron Loui a while ago (November 2007):
In Saint Louis, Missouri, (home of the renowned dialectician RPLoui) there is an apparently renowned restaurant The Seventh Inn owned by Else Barth, who shares the name of another renowned dialectician. And the association net is densified further since this was discovered by Bart Verheij (another dialectician who visited RPL) who lives in Paterswolde (near Groningen) where also Else Barth used to live.
The web says there was a fire in the restaurant so perhaps it no longer exists.
A typical blog entry to be tagged ‘leisure, argumentation’.
I have been reading in a special issue of Foundations of Science on the connections between argumentation and mathematics (Vol. 14, Nos. 1-2, 2009); guest editors Andrew Aberdein and Ian J. Dove. There is Andrew’s useful introduction to the issue, and also a paper by Alison Pease and colleagues on the computational representation of Lakatos’s proofs and refutations (see also Mandy Haggith’s ‘A meta-level argumentation framework for representing and reasoning about disagreement‘). Nice! Andrew gives pointers to Wilfrid Hodges’ text ‘An editor recalls some hopeless papers‘ on journal submissions disproving Cantor’s diagonal argument and to recent work by Erik Krabbe connecting pragmadialectics, argumentation and mathematics (‘Strategic Maneuvering in Mathematical Proofs‘; with a comment by Sally Jackson). Hodges refers to psychological work by Rips and also by Johnson-Laird and Byrne – about whose Deduction he is interestingly critical (“I know I am not alone in finding its accounts of logical theory almost incomprehensible”). Krabbe quotes Goethe:
Die Mathematiker sind eine Art Franzosen: redet man zu ihnen, so übersetzen sie es in ihre Sprache, und dann ist es alsobald ganz etwas anders.
Krabbe also discusses a ‘proof’ by mathematical induction that all horses have the same color.
Interesting, and simply: good fun.
In his paper Is logic empirical? Putnam has defended (Wikipedia: “at one point in his career”) that quantum logic is the ‘right’ logic from an empirical point of view. Quantum logic fails the principle of distributivity: p & (q v r) <=> (p & q) v (p & r).
