I discovered an interesting research program going on currently in the Adaptive Systems Group at the University of Hertfordshire, UK. A representative paper is "An integrated three-stage model towards grammar acquisition" by Yo Sato and colleagues, that appeared in the 2010 IEEE International Conference on Development and Learning. The paper documents an experiment in "cognitive robotics" where a robot is situated in a realistic language-learning environment.
According to the abstract, "the first, phonological stage consists in learning sound patterns that are likely to correspond to words. The second stage concerns word-denotation association. . . The data thus gathered allows us to invoke semantic bootstrapping in the third, grammar induction stage, where sets of words are mapped with simple logical types." This work is especially interesting to me because the grammar induction uses a semantic bootstrapping algorithm related to one which I developed, and published in 2005 (Journal of Logic, Language and Information).
In a discussion following my previous post, I offered the opinion that as computing power increases, we will (I hope) see more efforts to implement theoretically inspired learning algorithms that are quite intractable. This robotics paper represents one such effort, which I am very pleased to see. Yo Sato tells me that they are now looking at incorporating the improvements I have recently made to the original semantic bootstrapping algorithms. It's always gratifying to see an application inspired by my theoretical developments, since this is really why I pursue the work, but I am not sufficiently capable or interested to carry out the applied work that is then called for.