I am sure these are interesting references for studying pure mathematics but do they contribute significantly to solving AI?
In particular, it is interesting that none of your references mention any existing research on AI. Are there any practical artificial intelligence problems that these mathematical ideas have directly contributed towards solving?
E.g. Vision, control, natural language processing, automated theorem proving?
While there is a lot of focus on specific, mathematically defined problems on LessWrong (usually based on some form of gambling), there seems to be very little discussion of the actual technical problems of GAI or a practical assessment of progress towards solving them. If this site is really devoted to rationality should we not at least define our problem and measure progress towards its solution. Otherwise we risk being merely a mathematical social club, or worse, a probability based religion?
The main mystery in FAI, as I currently see it, is how to define its goal. The question of efficient implementation comes after that and depending on that. There is no point in learning how to efficiently solve the problem you don't want to be solved. Hence the study of decision theory, which in turn benefits from understanding math.
See the "rationality and FAI" section, Eliezer's paper for a quick introduction, also stuff from sequences, for example complexity of value.
This post enumerates texts that I consider (potentially) useful training for making progress on Friendly AI/decision theory/metaethics.
Rationality and Friendly AI
Eliezer Yudkowsky's sequences and this blog can provide solid introduction to the problem statement of Friendly AI, giving concepts useful for understanding motivation for the problem, and disarming endless failure modes that people often fall into when trying to consider the problem.
For a shorter introduction, see
Decision theory
The following book introduces an approach to decision theory that seems to be closer to what's needed for FAI than the traditional treatments in philosophy or game theory:
Another (more technical) treatment of decision theory from the same cluster of ideas:
Following posts on Less Wrong present ideas relevant to this development of decision theory:
Mathematics
The most relevant tool for thinking about FAI seems to be mathematics, where it teaches to work with precise ideas (in particular, mathematical logic). Starting from a rusty technical background, the following reading list is one way to start:
[Edit Nov 2011: I no longer endorse scope/emphasis, gaps between entries, and some specific entries on this list.]