I don't think it would be a good idea to focus obsessively on AIXI. If you want to study AI, study a broad set of topics. To find reading material, do a set of Google searches on obvious keywords and rank the results by citation count.
Regarding the papers, I have a very strong idiosyncratic belief about the path to AI: to succeed, researchers must study the world and not just algorithms. In my view, all results should be expressible in the form: because the real world data exhibits empirical structure X, algorithm Y succeeds in describing/predicting it. The algorithms presented by the papers you linked to probably work only because they happen to take advantage of some structure present in the toy problems they are tested on.
In my view, all results should be expressible in the form: because the real world data exhibits empirical structure X, algorithm Y succeeds in describing/predicting it.
AIXI does exactly that - it is based on Occam's razor.
I searched the posts but didn't find a great deal of relevant information. Has anyone taken a serious crack at it, preferably someone who would like to share their thoughts? Is the material worthwhile? Are there any dubious portions or any sections one might want to avoid reading (either due to bad ideas or for time saving reasons)? I'm considering investing a chunk of time into investigating Legg's work so any feedback would be much appreciated, and it seems likely that there might be others who would like some perspective on it as well.