A woman is listening to Sinatra before work. As she later describes it, ‘suddenly from nowhere I could hear my mother singing along to it … I was there again home again, hearing my mother … God knows why I should choose to remember that … then, to actually hear her and I had this image in my head … of being at home … with her singing away … like being transported back you know I got one of those (...) … like shivery feelings really suddenly’ (Anderson 2004, 9-10). An older couple, discussing their honeymoon forty years ago, each say that they can’t remember the show they saw, until through iterative, puzzled cross-cuing they finally get there – ‘Desert Song, that’s it’ (Harris et al 2011, 292). An elderly English veteran of a prisoner of war camp in Japan, finishing up morning tea with a young Japanese social scientist interested in reconciliation, suddenly calls out loudly - in Japanese - ‘stand to attention’. He stands to attention in front of her: like many of the men she interviews, he physically re-enacts fragments of that long-past world of the camp, bringing that absent past into this new present context with a visceral shock (Murakami 2001, 2012; Middleton & Brown 2005, 133-136). (shrink)

By pointing to deep philosophical confusions endemic to cognitive science, Wittgenstein might seem an enemy of computational approaches. We agree that while Wittgenstein would reject the classicist’s symbols and rules approach, his observations align well with connectionist or neural network approaches. While many connectionisms that dominated the later twentieth century could fall prey to criticisms of biological, pedagogical, and linguistic implausibility, current connectionist approaches can resolve those problems in a Wittgenstein-friendly manner. We present the basics of a Vector Symbolic Architecture (...) formalism, inspired by Smolensky, and indicate how high-dimensional vectors can operate in a context-sensitive and object-independent manner in biologically plausible time scales, reflecting Wittgenstein’s notions of language-games and family resemblance; we show how “soft” symbols for such a formalism can be formed with plausible learning cycles using Sparse Distributed Memory, resolving disputes surrounding Wittgenstein’s private language argument; and show how connectionist networks can extrapolate meaningful patterns to solve problems, providing “ways to go on” without explicit rules, which indicates linguistic plausibility. Connectionism thus provides a systematicity and productivity that is more than a mere implementation of a classical approach, and provides Wittgenstein-friendly and Wittgenstein-illuminating models of mind and language for cognitive science. (shrink)