"I can conceive of an ANN being trained to do classification and construction 
at the same time,"~Telmo 
Please explain how that would work.  I'm curious. ~PM

Date: Tue, 17 Feb 2015 14:48:12 +0100
Subject: Re: [agi] Couple thoughts
From: [email protected]
To: [email protected]



On Tue, Feb 17, 2015 at 10:24 AM, Piaget Modeler via AGI <[email protected]> 
wrote:



Classification: given a set of inputs return a distinct output that compresses 
the information of the input into a smaller set of values. 
Classification tasks can be done with neural networks, fuzzy logic, case based 
reasoning, specialized compression, etc.
Construction: given an initial state, a set of operations, and a goal state, 
return a sequence of operations that transforms the initial state into the goal 
state.
Right, I have no problem with the definitions of Classification and 
Construction. My problem is with the definitions of Intelligence, AI, and AGI. 
Can you define that? We need those definitions to be able to judge if 
Classification and Construction are necessary and sufficient for AGI. 
Construction tasks can be done with planning algorithms (state space search, 
plan space search, hierarchical search, etc.).

Both approaches ARE used in complex AI applications.
Yes, and if you look at what we know about how the human brain works, you can 
easily argue that the brain does Classification and Construction. What we don't 
know is if this will turn out to be a useful distinction. For example, I can 
conceive of an ANN being trained to do classification and construction at the 
same time, and without any well defined borders (as I suspect happens in the 
brain).
Or you could argue that Construction is all that's happening and that 
classification is just a detail to help construction (along with learning, 
random exploration, whatever).
Or...
My point is, this is just a model. Models aren't really right/wrong as much as 
they are useful or not.
Telmo. 
~PM

Date: Tue, 17 Feb 2015 09:03:40 +0100
Subject: Re: [agi] Couple thoughts
From: [email protected]
To: [email protected]



On Tue, Feb 17, 2015 at 8:42 AM, Piaget Modeler via AGI <[email protected]> 
wrote:



 I was taught that in AI there are two primary tasks, Classification and 
Construction.
Please correct me where I'm wrong, anyone.  I like to learn.
There has always been a lot of debate about what AI is. We don't even have 
anything close to a consensus on a good definition of "intelligence". This 
leads me to suspect that the main problem with AI is that we don't have a 
well-defined problem to tackle, but that's a broader issue.
Sure "Classification and Construction" is not so bad. It's not a matter of 
being right or wrong. There are thousands of plausible alternatives to this. 
You pick a model and run with it, but let's not pretend we are dealing with 
some super-objective definition. 
Deep Learning and (many other methods) are good at classification tasks.
We also need methods good at construction tasks (i.e. plan generation). 
This "also need" mentality could be the problem. Maybe what we need is 
something that can holistically perform both types of tasks.
Suppose you take deep blue. It can play chess really well, a skill that was up 
to then associated with humans. But then someone says: wait humans are also 
usually good at driving cars. Then you merge Google cars and deep blue and 
claim to be closer to AGI? Does this make any sense? Do you see the problem?
Best,Telmo. 
~PM

> Date: Mon, 16 Feb 2015 16:09:00 -0800
> Subject: [agi] Couple thoughts
> From: [email protected]
> To: [email protected]
> 
> I had a couple of things running through my mind --
> 
> 1) "Deep learning algorithms are very good at one thing today:
> learning input and mapping it to an output. X to Y. Learning concepts
> is going to be hard."    Andrew Ng.
> 
> I guess I take that to be an acid test of where the big guys are with 
> concepts.
> 
> 2) "brain inspired", "physics inspired", "math inspired," X-inspired,
> etc-inspired, hybird-inspired...
> 
> It seems all AGI approaches take the "inspired by" approach.  The only
> approach that is not deliberately inspired by some discipline, but
> aspires to the  actual thing:  Colin Hayes' approach.
> 
> There is nothing wrong with the "inspired by" approach, of course.
> 
> Mike
> 
> 
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