I’ve changed the name of the thread to focus it on the specific contents below.
Philip you also will need an explanation system in TalaMind, IMHO. An AIXItl system could also use one to explain its actions and perhaps to explain learned contexts. But where will the rules come from in English text which will be stitched together to write (or speak) the explanation?
AIXItl, even with its opaque semantics, could still be explained by theories which the Child can form independently of AIXItl. That seems to be what humans do; we justify our actions by stating our most fundamental beliefs – axioms in our theoretical model of the world. Showing how those beliefs interconnect to form a theory that explains most known experiences is an adequate explanation, IMHO. It isn’t necessary to correctly explain the Child’s actions, only to present to the User the Child’s current theories of why Baby acts like Baby does.
In other words, communications with users can be completely independent of the actual control system that seeks positive rewards and avoids negative ones.
How do you envision that in a TalaMind Child?
-Rich
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
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From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Friday, December 12, 2014 12:52 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Report of Ontolog Board of Trustees Meeting
Phil
Looking at your overview slides, I came across this one, which seems to support Child machine semantic construction concepts:
In addition to the Tala conceptual language, the architecture contains two other principal elements at the linguistic level:
•Conceptual Framework. An information architecture for managing an extensible collection of concepts, expressed in Tala.
•Conceptual Processes. An extensible system of processes that operate on concepts in the conceptual framework, to produce intelligent behaviors and new concepts.
I am very interested in the AIXItl algorithm, which is theoretically sufficient as a Child machine, but the model is based on a discrete sampled system – the canonical linear system model equations used by all control engineers and electrical engineers who process negative feedback systems. That makes it opaque how logic encodes knowledge and is fitted into the matrices of the linear system. It would be nice to have more meaningful ways of generating new concepts for the Child every time a new meaningful experience is encountered by said child.
But looking for building block concepts – those I can fit with others in wide varieties of ways – is pretty much without meaning unless linked in some way to experiences with said constructions. Those building blocks would necessarily have no individual meaning, and would have to draw their meaning from the context of the experience and from the outcome-to-initial-situation results.
Can you enlarge on the thesis ideas to cover how new concepts are created meaningfully in the Child machine version of TalaMind please?
Thanks,
-Rich
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
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