Hi, To repeat my earlier remarks, and add a few more:
On Mon, Mar 12, 2018 at 3:42 PM, Alexey Potapov <pas.a...@gmail.com> wrote: > > Yes. But Pattern Matcher compares all pairs of bounding boxes making it > quadratic. Yes, there is supposed to be a space-server that is supposed to be optimized for these kinds of searches. There is one, but its super-minimal, and not at all integrated with the pattern matcher, or anything else for that matter. Smart searches on bounding boxes is completely green-field development, for the atomspace. We've kind of got very nearly nothing for this. >> Yes, but keep in mind that the PM is also Turing complete because you can >> call any function within a query (including the PM itself). > > This is quite problematic. Basic processes should not execute anything > dangerous that can take too much time or loop forever and cannot be > interrupted. Thus, we should either not treat PM as a basic process, or > should restrict its capabilities (and shift responsibility for evaluating > arbitrary code to other processes). This is misleading or a mis-understanding. Its not the correct way to think about it. The current pattern matcher is 2 or three or 4 things matched into one: A) A generic subgraph isomorphism solver. Since this is an NP complete problem, it's certainly possible to create pathologically slow queries. B) A way of combining subgraphs using a crisp-logic boolean algebra (actually a Heyting algebra) which we have very vague intentions of promoting into something probabilistic. Which, of course, if this was done, would layer on an additional combinatoric explosion. It would be fruitful to discuss the wisdom or stupidity of this particular task. Or alternative designs for it. C) The ability to perform subgraph isomorphism with so-called "axiom schemata". An "axiom schemata" is roughly an infinite collection of relations, for example "less than" over the integers or rationals or reals. This means that the pattern matcher is kind-of-like-ish a "satisfiability modulo theories" (SMT) solver. The API for specifying a theory at this point is rather very simplistic. The "virtual link" is that API. It says, basically "implement your model theory here, as C++ code, and we will automatically do the satisfiability modulo your theory for you" Currently supported theories are the equational theory (EqualLink) and numeric inequaltiy (GreaterThanLink) An example of a nice-to-have theory would be linear algebra - done right, this could solve your space-time bounding box problem for starters, and linear programming type problems if anyone cared about that. Maybe matroids. Whatever. Dunno. Another nice-to-have would be naive set theory which could help lay a cornerstone of probability done right (TM) but this would be a long and difficult but veryinteresting discussion. D) Once a matching subgraph is found, you can launch arbitrary C++/scheme/python code to do something with that subgraph. So that's unbounded. >> So, the first thing you should do is build a good benchmark tool, then we, >> you and the rest of opencog community, can supply it with a collection of >> critical tests. > > How do you see such tool? Unclear. I am interested in a tool that tells me if performance got worse after a particular code change or bug fix. Some of our fixes accidentally slow things down (by a lot) and no one noticies for months or half a year. > We have some datasets of varying sizes and > queries, and simply run PM on these queries and measure the time. What can > be unified/automated? Yes!? > Running all tests and writing log files with > computation times? Anything else? I don't care about log files. > I agree that we need several (many?) tests to be sure that some changes > didn't affect any types of queries, but isn't it just a script? Or do you > have something much more complicated in mind? Take a look at 3D graphics performance: there are two types of benchmark: triangles per second, lines per second, texture maps per second. The other type is "for game XYZ, frames per second". We need both types of benchmarks. Probably the first more than the second, because it helps developers more. The second kind just tells you how screwed up the system is today, without telling you why, or where to look. > In our case, the query processing time becomes unrealistically large for a > one-minute video. If we consider the problem of search in the entire > episodic memory, it should be even not linear, but logarithmic. Low degree > polynomial complexity is ok for the task dimensions ~1000, not millions or > billions... No clue what you are searching here. Logarithmic searches mean binary tree, quad-tree, octree. The space-time sever is an octree, but its not integrated with the pattern matcher, and has a super-naive API. We have binary-trees and hash tables for atoms-by-name, by-type, but zero sophistication for numeric values. See above comments about "satisfiability modulo theories". > OK, then, we will study PM for now. > Right now, I can only make some contradictory guesses. Maybe, there is a > simple yet general heuristic, which fixes our case (surely, not all possible > cases, but maybe they are not too frequent). Maybe, we need another specific > algo and data structures to retrieve from episodic memory. Maybe, we need a > sort of specializer, that can project the general PM on a specific query (in > our case, to consequently enumerate all frames and to compare BBs inside > them). Maybe we should do everything via callbacks implemented in Atomese... > Also, I'm starting to think about possible merging of PM with Sampling. > Indeed, queries are non-deterministic programs with variables as random > choices conditioned on a set of clauses... But I'm not sure it is > technically sensible to put it in such way... > > -- Alexey Linas. -- cassette tapes - analog TV - film cameras - you -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to opencog+unsubscr...@googlegroups.com. To post to this group, send email to opencog@googlegroups.com. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CAHrUA34HGqQmuVnjfe0GnXryWQh4T1-7A30%2BxZ6Zk3SZ_4MRvQ%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
