For the sake of completion  ;)

Nils Bertschinger's work 
https://github.com/bertschi/ProbClojureNice 
https://groups.google.com/forum/?fromgroups=#!topic/clojure/9NhsFga4D9s

Le mercredi 24 avril 2013 11:34:14 UTC+2, Zack Maril a écrit :
>
> Lately, I've been on a bit of a jag into probabilistic programming with 
> Clojure, specifically embedding Church inside of Clojure. The results so 
> far are promising from a syntactic level, but, like David said, getting it 
> to actually work is another matter entirely. I wanted to share what I've 
> been able to get working so far and some of the potential challenges of 
> embedding Church in Clojure. 
>
> https://gist.github.com/zmaril/5447488
>
> The above gist is a self contained Clojure program that implements, among 
> other things, `query-by-rejection` and `flip`. With these two functions, we 
> can already do most of what Church seems to do. What's missing from 
> a functionality standpoint is support for various distributions and some 
> useful functions related to tolerance (and, of course, a good MCMC/Gibbs 
> implementation). What's been gained is, via some careful macro writing, the 
> ability to reuse code, specifically to reuse memoized functions. 
>
> One of the key ideas behind Church is that memoization allows one to 
> express complicated scenarios very concisely. So, to code up a randomized 
> persistent trait (like a person's eye color), you simply define a memoized 
> function that takes in a person and returns their eye color. Every time a 
> new world is generated, the memoized function gets recreated. But within 
> the world (or current experiment), the trait persists and can be referenced 
> again in various places without too much hassle.  Note that a new memoized 
> function must be created for each experiment, i.e. you can't just memoize 
> the function outside the query and bring that back in. Within the gist 
> above, binding is used to carefully rebind any function provided in the 
> :memobound clause for each experiment. By declaring a var to be dynamic, we 
> can write queries that are pretty short but all rely on the same logic. 
> From a syntactic standpoint, it took about one evening of work to cut down 
> the length of most of the Church examples by at least half. 
>
> From a speed standpoint, Church is way, way ahead of the above. Sampling 
> via rejection is quite slow compared to modern methods like MCMC or Gibbs. 
> It might not even be possible to do the dynamic rebinding of memoized 
> functions mentioned above and get as fast as Church is. I really don't 
> know. Here's one of the first papers on Church:
> http://www.stanford.edu/~ngoodman/papers/churchUAI08_rev2.pdf
>
> The paper is about five years old now, but section 4.1 goes into how 
> Church was first implemented with a MCMC. The key idea they introduce here 
> is the computation trace. I won't try to summarize it here because I don't 
> fully understand it yet. If it means what I think it means though, then it 
> should be possible to build and keep track of the computation trace thanks 
> to the JVM and Clojure. My intuition says that a very dedicated student 
> could probably produce a Clojure library to catch Church in terms of speed 
> by the end of the summer, simply by emulating what they have done and 
> letting pmap take care of the rest.  
> -Zack
>
> On Wednesday, April 24, 2013 12:48:56 AM UTC+4, David Nolen wrote:
>>
>> On Tue, Apr 23, 2013 at 2:10 PM, Radosław Piliszek <radzi...@gmail.com>wrote:
>>
>>> 1) Is this place the best to discuss this?
>>>
>>
>> Yes.
>>  
>>
>>> 2) Are there some set goals that CLP(Prob) should achieve? (,,Basic 
>>> support of CLP(Prob).'' does not express it too well! :-P )
>>>
>>
>> This seems like a pretty challenging one as there are a variety of 
>> possible approaches. Basic support for CLP(Prob) could very well mean 
>> *several* prototypes. That said the probabilistic Prolog variants are 
>> probably worthy of the most study as core.logic is closest to that model.
>>  
>>
>>> 3) Is there any API sketch that should be followed? Is it still yet to 
>>> be discussed? And, most importantly, how would you see CLP(Prob) fit in 
>>> core.logic's ecosystem?
>>>
>>
>> There is no API sketch. It's extremely important to survey the links, try 
>> out existing implementations, assess their advantages / disadvantages and 
>> devise a syntax (or several) that works reasonably well with what we've 
>> already established in core.logic. 
>>
>> Of the projects listed this is probably the most experimental and 
>> research-y. I think if anyone seriously wants to take this on they have to 
>> be extremely focused / self-directed and be willing to put in a 
>> *considerable* amount of time. I'm of course willing to help in whatever 
>> way I can as far as implementation & integration approach - but it will be 
>> a big learning experience for me as well!
>>
>> David
>>
>

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