[ivanv]

I'm doing some work on behaviour of AI. Particularly on recognition of user intension. I thought that somehow mood about some intension has to be recorded. So a solution came to my mind: to align all doings according to "wanting to know and predict input as much as possible". And that could be the opposite side of "fearing of unknown input". Something like reinforcement learning.
But what if, for predicting input, machine uses some autoritative measures like "do that or else  ". I'm wandering is there some workaround?

[ivanv]

some experiments with data formatting and visual representation (no, it's not off topic, it's about data!):



 

[ivanv]

oh, yes, just for completeness, although it was already published under "ethic" topic


 

[ivanv]

Hello everyone!
I'm in dilemma. Do you consider last two posts as spam material? should I delete them?

[Freddy]

Hey, no not spam by any means, just busy at the moment so haven't commented... perfectly fine by me 

[Bragi]

I'm still wondering what you used to make the videos?

[ivanv]

I'm still wondering what you used to make the videos?

first two videos are made in xara designer.
third one is made in swish max (for creating flash content)

[Bragi]

The first one sort of reminds me of pivot tables.
The second, I don't really understand what you are trying to say, though it does remind me of how I represent data sometimes. Are you looking for, trying to or have developed a set based database system?
 Here's an old image (but still mostly valid) of mind map editing in my neural network designer:

The blue one is a cluster of type 'object'. It contains a text neuron with the value 'me' and a regular neuron that's simply labelled 'me'. the object links to a neuron labeled 'home' and the link has a meaning of 'at', so you can read it as 'me at home' 

[ivanv]

Are you looking for, trying to or have developed a set based database system?

just for a while now, i'm experimenting with different formats for storing knowledge base, which i find very important for artificial intelligence. i test these formats on real-world commercial demands. once i have a complete system for knowledge base, i'll move to next step - implementing behaviour mechanism. i have no interest in commercial application development (at least for now), but i would be happy to participate with the idea.

the first video  shows a sort of inheritance mechanism known from OOP

the second video shows  how knowledge base could be defined through sets and N:1 relations known from relational databases. some background knowledge about databases in required to spot progress over current technology (SQL). but as for ai, the principle is this: each set has elements. each element can be connected to elements of other set through relations.
<below, in attachment is example>

well, first two videos show separately element in sets (first video) and definition of that elements (second video). my next station is to merge those two concepts into one single diagram. also, some dynamics for data are ought to be added. wish me luck 

[ivanv]

as i was fastly enter the trusty member hall, i'm trying to prove myself a hard time. i was experimenting with that graph representation of knowledge. look at what i managed to construct with paradigm i called binary relational modeling (brm). brm has its own dedicated site under construction where that paradigm is being described in detail.

[infurl]

as i was fastly enter the trusty member hall, i'm trying to prove myself a hard time. i was experimenting with that graph representation of knowledge. look at what i managed to construct with paradigm i called binary relational modeling (brm). brm has its own dedicated site under construction where that paradigm is being described in detail.

Here is an article about data modelling and conceptual schemas that may help you, in case you haven't already come across it.

http://en.wikipedia.org/wiki/Conceptual_schema

[ivanv]

Here is an article about data modelling and conceptual schemas that may help you, in case you haven't already come across it.

http://en.wikipedia.org/wiki/Conceptual_schema

boy, you scared me, particulary with this one: http://en.wikipedia.org/wiki/Concept_mapping. but i'm dealing with sets having elements and binary relations, not with concepts and n-ary relations. after folowing some links, i concluded that my brm isn't  subset of any graphing methods i found in wiki about conceptual schemas, or at least it differs in groundings.

these are example relationships i found on wiki:

    Each PERSON may be the vendor in one or more ORDERS.
        - done with brm (essence)
    Each ORDER must be from one and only one PERSON.
        - done with brm (essence)
    PERSON is a sub-type of PARTY.
        - requires complicating brm (not an option despite of expressive power)
        - will be implemented in superduper knowledge representation base that will hold brm also
    Each Employee may have the supervisor within Employee.
        - done with brm (by recursion)

anyway, thanks for watching and for information that i might not been wasting time. 

[ivanv]

i just googled "binary relational model" and it happend! i invented hot water!

link 1: http://c2.com/cgi/wiki?SemanticBinaryModel
"Semantic Binary Model" is "A database model proposed by Dr Naphtali David Rishe.". it sounds just like brm and page was written in 2009.

link 2: http://dl.acm.org/citation.cfm?id=1575688
"The Use of the Binary-Relational Model in Industry: A Practical Approach"". a book from 2009

link 3: http://dl.acm.org/citation.cfm?id=636814
"The Semantic Binary Relationship Model of information". this is my favourite. the book dates from 1984!

... and so on ...

the damn thing is full of that stuff!  no, it's not funny!

anyway, if you think it deserves a look here is my own link:
https://sites.google.com/site/binaryrelationalmodeling/
 

[ivanv]

here is a little presentation of how true ai would be implemented.
very breaf, 5 pages, no basic knowledge required:
https://sites.google.com/site/ivanvodisek/AI-goal.swf

[Genesis]

here is a little presentation of how true ai would be implemented.
very breaf, 5 pages, no basic knowledge required:
https://sites.google.com/site/ivanvodisek/AI-goal.swf

You need a little bit more specificity. Its too general. Too broad.
Have you tested the theory? What are the results?

Edit:

My theory is similar to yours but my end goal is quite different. You are working on recognizing people's intentions. While I'm working on an AGI system that would also be able to not only recognize people's intents, but also recognize what they know and predict what actions they are going to make based on what they know.