>
> Could you explain (with enough  detail) how it is more natural?  I am very
> much interested in allowing natural expressivity in the atomspace.
>

Here is an example
https://github.com/trueagi-io/hyperon/blob/0534d9590e8e0bc25967d6810bd525b415e2d19f/python/tests/test_minecraft.py#L80-L101.

The task here is to craft wooden-pickaxe in minecraft, but just see how
Vitaly introduces "if" into the knowledge base:

(= (if True $then $else) $then)
> (= (if False $then $else) $else)














































ср, 28 апр. 2021 г. в 21:37, Linas Vepstas <[email protected]>:

>
>
> On Wed, Apr 28, 2021 at 5:17 AM Anatoly Belikov <[email protected]>
> wrote:
>
>> Planning in my example didn't work due to certain assumptions being made
>> in URE. So let's say URE comes up with a nested bindlink like that:
>>
>> (ExecutionOutputLink(stack c a)
>> ...
>>     (ExecutionOutputLink(stack a b)
>>         (ExecutionOutputLink (pickup a) ) )
>>
>> When it evaluates (stack c a) all atoms introduced by(stack a b)  and
>> (pickup a) are present in the atomspace. So preconditions of stacking c on
>> a are not satisfied(a is both being 'held' and not 'held'). Probably there
>> is a simple workaround like placing all new facts into separate
>> ContextLink. Such simple planning problems are more naturally expressed in
>> new opencog-hyperon,
>>
>
> Could you explain (with enough  detail) how it is more natural?  I am very
> much interested in allowing natural expressivity in the atomspace.
>
>
>> so I lost the motivation for turning URE into a planner.
>>
>
> It is not at all obvious that the URE is a suitable platform for being a
> planner, anyway -- certainly, I would not have recommended that course of
> action.
>
> Planning can be viewed as a form of a constraint satisfaction problem, and
> the best constraint satisfaction solver that I know of is ASP, and
> specifically, the Potsdam solver. It is ideal for solving anything with
> crisp-boolean constraints.  It does have some callbacks that should allow
> it to work with "fuzzy" constraints, but I have never tried these.
>
> I would like to advocate that, for planning and for constraint
> satisfaction, that the Potsdam solver should be integrated so that it can
> work with declarative data in the AtomSpace.  This would make it "kind of
> like" the URE, but really quite different in many ways.
>
> I don't think that writing a new planner, either in Hyperion or in the
> atomspace, is a good idea. You will almost certainly create something that
> is 1000x slower than the best solvers available today.  I want to
> illustrate this with a story.
>
> In the 1980's, electronic circuit simulation (i.e. chip design rule
> verification) was done using backward/forward chaining, similar to what the
> URE does. This was a very established technique, a multi-billion dollar
> industry with half-a-dozen vendors and another half-a-dozen in-house,
> proprietary solutions. In the late 80's, early 1990's, new planners and
> verifiers were created using SAT solvers. For chips of that era (about 500K
> transistors) the SAT solvers and the backward/forward chainers were about
> equal in performance. For chips with 2M transistors, the SAT solvers were
> 2x or 4x faster than the backward-forward chainers.  For chips with >5M
> transistors, SAT was 10x, 20x faster than backward/forward, and the
> established chip-planner and verification houses were going bankrupt,
> because all of their customers had transitioned to the new SAT solver
> technology.
>
> This is a multi-billion dollar lesson in technology, and you ignore it at
> your own peril.  Trying to reinvent your own planner is perhaps a good
> homework exercise to learn basic principles, but it is not sound software
> engineering.  I very strongly advise against it.
>
> Now, PLN is a bit different. It was intended to work with probabilities,
> instead of crisp true/false values. This does make the problem harder.
> However, I think there are plenty of clever things one can do, without
> resorting to backward-forward chaining.  Examples include:
>
> * Given some inputs and rules, assign random crisp true/false values to
> them (according to a probability distribution), and use ASP to solve the
> problem.  Repeat 100 times, and take the average. The desired result is
> that average.
>
> * Most probabilistic problems can be split into two parts: one that is
> "almost crisp t/f" (the hard constraints) and the fuzzy, soft constraints.
> Use ASP to solve the crisp parts, and explore the fuzzy/soft parts
> systematically.
>
> Now, what I say above is "easy to say" but is "hard to do" -- implementing
> what I suggest is a large project.  But then, in software, nothing is free.
> facebook and google and amazon employ thousands of engineers because
> writing good software is hard. Imagining that you can create a new planner
> out of thin air in a few months is not a realistic dream. Don't repeat
> history; learn from it.
>
> -- Linas
>
> Besides all planners rely on heuristics to guide the search, so even if
>> you will make URE work on this particular small example you'll have to do
>> some more work to integrate them in URE.
>>
>>
>>
>> ср, 28 апр. 2021 г. в 12:38, Michele Thiella <[email protected]>:
>>
>>> Hello Nil, hello Linas and hello everyone,
>>>
>>> First of all, Nil, I have spoken to my supervisors and unfortunately I
>>> will not be able to develop your ROCCA project.
>>> I'll try to follow the developments, since you explained to me how the
>>> code works (thanks again).
>>>
>>> Instead, I focus on solving the blocksworld problem (and then expand the
>>> project by adding communication)
>>> So, I'm studying how URE inference works.
>>> My test repository can be found here:
>>> https://github.com/raschild6/blocksworld_problem
>>>
>>> I don't understand what I'm doing wrong ..
>>>
>>> - Why the backward chaining fails to resolve the goal?
>>> - Also, I think I don't quite understand how fuzzy conjunction
>>> introduction and elemination rules work.
>>>
>>> I have other questions related to the URE log but for now I would like
>>> to understand these.
>>>
>>> (I don't know if it's better to open a new conversation)
>>> Thanks again for your help, sorry for the inconvenience!
>>>
>>> Michele
>>>
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>
>
> --
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> Sponge Bob: No, Patrick, they are laughing next to us.
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