I've found that I learn new topics best by struggling to understand a jargoney paper.  This passed through my inbox today and on the surface it appears to hit a lot of high notes.

Since I'm not an expert, I have no idea if this has any depth to it.  Hivemind thoughts?

Modeling Human Decision Making using Extended Behavior Networks, Klaus Dorer

(Note: I'm also pushing myself to post to LW instead of lurking.  If this kind of post is unwelcome, I'm happy to hear that feedback.)

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6 comments, sorted by Click to highlight new comments since: Today at 8:23 PM

Not being in the field, but having experience in making the judgement "Should I read this paper", here are a handful of observations:

For:

  1. The paper has a handful of citations not entirely from the author (http://scholar.google.com/scholar?cites=8141802968877948536&as_sdt=2005&sciodt=0,5&hl=en) but by no means a huge number of citations.

  2. The abstract is remarkably clear (it's clear that this is a slight extension of other author's work), and the jargon-y words are easily figured out based on gentle perusal of the paper.

  3. It looks like this paper is actually also a chapter in a textbook (http://link.springer.com/chapter/10.1007/978-3-642-11876-0_8)

Against:

  1. Nearly half of the paper's (very few) references in its reference section are self-citations.

I'd say it's worth reading if you're interested in it. Even the against-point above is more of a general heuristic and not necessarily a bad thing.

Even I have a chapter in a textbook, its not a measure of quality :) Conference proceedings sometimes are published as a book, with ISBN and all.

Thank you. Heuristics like these are, I think, the meta-skill I'm trying to learn at the same time.

Not unwelcome.

Seconding a lot of calef's observations.

If the new topic you want to learn is "extended behavior networks", then maybe this is your best bet. But if you really want to learn about something like AI or ML or the design of agents that behave reasonably by the standards of some utility-like theory, then this is probably a bad choice. A quick search in Google Scholar (if you're not using this, or some equivalent, making this a step before going to the hivemind is a good idea) suggests that extended behavior networks are backwater-y. If the idea of a network of things interacting to make a decision appeals to you, maybe look into Petri nets or POMDPs. Or better yet, start with something like Russel and Norvig's AIMA to get a better view of the landscape. If the irrationality part is interesting, start with Kahneman, Slovic, and Tversky's Judgment under uncertainty: Heuristics and biases, which gives you a curated collection of jargoney papers.

I would prefer that this kind of very specific question was a comment in an open thread rather than a top-level post. There seems to be some general push for more top-level posts, which I think is mistaken.