25.5 from now, i hope :)
Il giorno giovedì 1 aprile 2021 alle 19:29:39 UTC+2 [email protected] ha
scritto:
9pm EET works for me.. is that 1.5 hours from now or 25.5 hours
from now?
On Thu, Apr 1, 2021 at 8:19 AM Michele Thiella <[email protected]>
wrote:
Could it be around 9pm EET?
it's a completely different time but should it be available for
everyone?
Michele
Il giorno giovedì 1 aprile 2021 alle 16:29:53 UTC+2 Nil ha scritto:
Sure! The place is
https://meet.jit.si/proto-agi <https://meet.jit.si/proto-agi>
the time is
10:45am EET
Unfortunately probably too early if you're in the US.
Michele, maybe we could do a last minute change to fit the
US timezone
as well? With the risk of adding confusion though.
I'll try to record the call, BTW.
Nil
On 4/1/21 5:08 PM, Douglas Miles wrote:
> May I sit in on the meeting as a fly on the wall?
> If so, when/how shall I connect?
>
> Thanks in advance!
> Douglas Miles
>
> On Thu, Apr 1, 2021 at 2:52 AM Michele Thiella
<[email protected]
> <mailto:[email protected]>> wrote:
>
> Hi Nil,
> you're right! currently EET corresponds to the Italian time!
> Great, then I might be a few minutes late because I have
a lesson
> first. But surely 10.45am EET can work!
>
> Also for me, no problems for those who want to join!
> Thanks for the PLN link. See you tomorrow.
>
> Michele
> Il giorno mercoledì 31 marzo 2021 alle 14:40:38 UTC+2 Nil
ha scritto:
>
> Hi Michele,
>
> On 3/27/21 12:12 PM, Michele Thiella wrote:
> > Is there any recommended book/paper to study before the
code
> of PLN rules?
>
> Search for Probabilistic Logic Networks in
>
>
https://wiki.opencog.org/w/Background_Publications#Books_Directly_Related_to_OpenCog_AI
<https://wiki.opencog.org/w/Background_Publications#Books_Directly_Related_to_OpenCog_AI>
>
<https://wiki.opencog.org/w/Background_Publications#Books_Directly_Related_to_OpenCog_AI
<https://wiki.opencog.org/w/Background_Publications#Books_Directly_Related_to_OpenCog_AI>>
>
>
> > For the meeting, could it be at 11.30am EET?
>
> 11:30am EET works for me. But maybe you mean 10:30am EET.
With
> daylight saving time it seems EET corresponds to Italy
time. I'm
> not
> sure so double check but anyway 10:30am Italy time works
for me.
>
> Nil
>
> >
> > Michele
> >
> > Il giorno venerdì 26 marzo 2021 alle 08:56:11 UTC+1 Nil ha
> scritto:
> >
> > On 3/25/21 9:03 PM, Michele Thiella wrote:
> > > Can I ask you to say something about tree of
decisions in Eva?
> > Was it a
> > > separate scheme/python module that analyzed
SequentialAnd?
> > > While i'm at it, I can't place some components in your
> architecture:
> > > I read Moshe Looks thesis on MOSES and what I found on
> OpenPsi.
> > But in
> > > practice what were they used for?
> >
> > MOSES is a program learner. In principle it could learn
any
> program, in
> > practice it is mostly used to learn multivariable boolean
> functions (as
> > it doesn't work very well on anything else, so far
anyway).
> >
> > See for more info
> >
> >
>
https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search>
>
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search>>
>
> >
>
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search>
>
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search
<https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search>>>
>
> >
> >
> > > Finally, in practice what does PLN do/have more than
URE?
> >
> > The URE is a generic rewriting system, that needs a
rule set to
> > operate.
> >
> > See for more info
> >
> > https://wiki.opencog.org/w/Unified_rule_engine
<https://wiki.opencog.org/w/Unified_rule_engine>
> <https://wiki.opencog.org/w/Unified_rule_engine
<https://wiki.opencog.org/w/Unified_rule_engine>>
> > <https://wiki.opencog.org/w/Unified_rule_engine
<https://wiki.opencog.org/w/Unified_rule_engine>
> <https://wiki.opencog.org/w/Unified_rule_engine
<https://wiki.opencog.org/w/Unified_rule_engine>>>
> >
> > Such rule set can be PLN, which has been specifically
> tailored to
> > handle
> > uncertain reasoning
> >
> > https://github.com/opencog/pln
<https://github.com/opencog/pln>
> <https://github.com/opencog/pln
<https://github.com/opencog/pln>>
<https://github.com/opencog/pln
<https://github.com/opencog/pln>
> <https://github.com/opencog/pln
<https://github.com/opencog/pln>>>
> >
> > or the Miner, which is has been tailored to find frequent
> subgraphs
> >
> > https://github.com/opencog/miner
<https://github.com/opencog/miner>
> <https://github.com/opencog/miner
<https://github.com/opencog/miner>>
> <https://github.com/opencog/miner
<https://github.com/opencog/miner>
> <https://github.com/opencog/miner
<https://github.com/opencog/miner>>>
> >
> > or more, though these are the two most used/mature.
> >
> > Nil
> >
> > >
> > >
> > > Before reasoning is possible, one must have a
world-model.
> This
> > > model has several parts to it:
> > > * The people in the room, and their 3D coordinates
> > > * The objects on the table and their 3D coordinates.
> > > * The self-model (current position of robot, and of its
> arms, etc.)
> > > The above is updated rapidly, by sensor information.
> > >
> > > Then there is some long-term knowledge:
> > > * The names of everyone who is known. A dictionary
linking
> names to
> > > faces.
> > >
> > > Then there is some common-sense knowledge:
> > > * you can talk to people,
> > > * you can pick up bottles on a table
> > > * you cannot talk to bottles
> > > * you cannot pick up people.
> > > * bottles can be picked up with the arm.
> > > * facial expressions and arm movements can be used to
> communicate
> > > with people.
> > >
> > > The world model needs to represent all of this. It also
> needs to
> > > store all of the above in a representation that is
> accessible to
> > > natural language, so that it can talk about the
position of
> its arm,
> > > the location of the bottle, and the name of the
person it is
> > talking to.
> > >
> > > Reasoning is possible only *after* all of the above
has been
> > > satisfied, not before. Attempts to do reasoning
before the
> above
> > > has been built will always come up short, because some
> important
> > > piece of information will be missing, or will be stored
> somewhere,
> > > in some format that the reasoning system does not have
> access to it.
> > >
> > > The point here is that people have been building
"reasoning
> systems"
> > > for the last 30 or 40 years. They are always frail and
> fragile. They
> > > are always missing key information. I think it is
> important to try
> > > to understand how to represent information in a uniform
> manner, so
> > > that reasoning does not stumble.
> > >
> > >
> > > Atomspace:
> > >
> > > Concepts: "name" - "3D pose"
> > > - bottle - Na
> > > - table - Na
> > > (Predicate: "over" List ("bottle") ("table"))
> > > Actions:
> > > - Go random
> > > - Go to coord
> > > - Grab obj
> > >
> > > Goal: (bottle in hand) // = grab bottle
> > >
> > > Inference rules: all the necessary rules, i.e.
> > > * grab-rule: preconditions: (robot-coord = obj-coord)
...,
> > > effects: (obj in hand) ...
> > > * coord-rule: if x is in "coord1" and y is over x
then y is in
> > > "coord1"
> > >
> > > -> So, robot try backward chaining to find the behavior
> tree to
> > > run. It doesn't find it, it lacks knowledge, it
doesn't know
> > > where the bottle is (let's leave out partial trees).
> > > -> Go random ...
> > > -> Vision sensor recognizes table
> > > -> atomspace update: table in coord (1,1,1)
> > > -> forward chaining -> bottle in coord (1,1,1)
> > > -> backward chaining finds a tree, that is
> > > Go to coord (1,1,1) + Grap obj
> > > -> goal achieved
> > >
> > >
> > > This is a more-or-less textbook robotics homework
> assignment. It has
> > > certainly been solved in many different ways by many
different
> > > people using many different technologies, over the last
> 40-60 years.
> > > Algorithms like A-star search are one of the research
> results of
> > > trying to solve the above. The AtomSpace would be a
horrible
> > > technology to solve the above problem, its too slow, too
> bulky, too
> > > complicated.
> > >
> > > The chaining steps can be called "inference", but it is
> inference
> > > devoid of natural language, devoid of "true
understanding".
> My goal
> > > is to have a conversation with the robot:
> > >
> > > "What do you see?"
> > > "A bottle"
> > > "where is it?"
> > > "on the table"
> > > "can you reach it?"
> > > "no"
> > > "could you reach it if you move to a different place?"
> > > "yes"
> > > "where would you move?"
> > > "closer to the bottle"
> > > "can you please move closer to the bottle?"
> > > (robot moves)
> > >
> > >
> > > This is now clear to me, but why natural language?
> > > if i didn't want interactions with humans could i do it
> differently?
> > > A certain variation of the sensor values already
represents
> "the
> > forward
> > > movement", I do not need to associate a name with it
if I
> don't
> > speak,
> > > also for the Atom "bottle" I could use its ID instead.
> > > I don't understand why removing natural language implies
> having an
> > > inference devoid of "true understanding".
> > >
> > > Stupid example: If I speak Italian with a French,
neither
> of us
> > > understands the other. But a bottle remains a bottle for
> both and
> > if I
> > > give him my hand he will probably do it too ... or he
will
> leave
> > without
> > > saying goodbye.
> > >
> > > I'm probably missing something big, but until I don't
bang
> my head
> > > against it, I don't see.
> > >
> > >
> > > This can be solved by carefully hand-crafting a chatbot
> dialog tree.
> > > (The ghost chatbot system in opencog was designed to
allow
> such
> > > dialog trees to be created) Over the decades, many
chatbots
> have
> > > been written. Again: there are common problems:
> > >
> > > -- the text is hard-coded, and not linguistic. Minor
> changes in
> > > wording cause the chatbot to get confused.
> > > -- there is no world-model, or it is ad hoc and
scattered
> over many
> > > places
> > > -- no ability to perform reasoning
> > > -- no memory of the dialog ("what were we talking
about?" -
> well,
> > > chatbots do have a one-word "topic" variable, so the
> chatbot can
> > > answer "we are talking about baseball", but that's it.
> There is no
> > > "world model" of the conversation, and no "world
model" of
> who the
> > > conversation was with ("On Sunday, I talked to John
about a
> bottle
> > > on a table and how to grasp it")
> > >
> > > Note that ghost has all of the above problems. It's not
> linguistic,
> > > it has no world-model, it has no defined representation
> that can be
> > > reasoned over, and it has no memory.
> > >
> > > 20 years ago, it was hard to build a robot that could
grasp a
> > > bottle. It was hard to create a good chatbot.
> > >
> > > What is the state of the art, today? Well, Tesla has
> self-driving
> > > cars, and Amazon and Apple have chatbots that are very
> > > sophisticated. There is no open source for any of this,
> and there
> > > are no open standards, so if you are a university grad
> student (or a
> > > university professor) it is still very very hard to
build a
> robot
> > > that can grasp a bottle, or a robot that you can talk
to.
> And yet,
> > > these basic tasks have become "engineering"; they are no
> longer
> > > "science". The science resides at a more abstract
level.
> > >
> > > --linas
> > >
> > >
> > > I find the abstract level incredible, both in terms of
> beauty and
> > > difficulty!
> > >
> > > Michele
> > >
> > > --
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