Welcome to crowd, Yan King Yin. I was also severally p*d off when I finally put 
my AGI architecture thoughts together in what I thought was a very coherent 
format (but had to split it over two papers because of length restrictions) and 
it was rejected mainly because I didn't reference enough others and because 
there was no proof of concept. Took me a while to get over that (As an academic 
I have published over 200 papers in my 'other life' i.e. mainstream work) as I 
was really proud of what I had written and I thought it would have stimulated 
debate. But yes, it seems some (most?) of the AGI reviewers are more concerned 
about the format and using mainstream 'proper academic criteria' than the 
novelty and potential insights and contribution and original thinking - despite 
what they claim as being one of the conference goals. That was more than 5 
years ago and you can see I'm still feeling sore about it. I can only recommend 
that you don't let it influence your personal commitment and drive and 
inspiration (given that it demotivated me for a while and took me quite a few 
years to rediscover my mojo). Try to ignore them and find a friendlier or more 
open-minded audience.

Best - Jean-Paul


________________________________
From: YKY (Yan King Yin, 甄景贤) <[email protected]>
Sent: Monday, 17 June 2019 07:10
To: AGI
Subject: Re: [agi] My AGI 2019 paper draft

I am really disappointed that my AGI 2019 paper has been rejected.  The reasons 
given by the reviewers are very superficial and vacuous, and given that I have 
posted my presentation slides here which explained the theory in very simple 
terms, and they have not given me a chance to explain any unclear details to 
them (it could be argued that they lack certain basic AGI background notions, 
and it's not my fault to omit them).  Either the reviewers don't understand my 
ideas or they are biased by political reasons.

Anyway, I will continue to publish my ideas through other channels, to the 
global community.  See you around 😅

PS:  my paper has an unconventional style which was *deliberate* to make it 
more understandable.

----------------------- REVIEW 1 ---------------------
SCORE: 1 (Weak Accept)

1. The paper is not in the required format.

2. The paper only described what is included in the proposed model, but does 
not clearly explain how these parts work together as a complete system, nor 
that why the system can be taken as an AGI.

3. Not sure how "inductive bias" is implemented in the system? Is it "learned" 
by the system during the learning process, based on a control mechanism of the 
system, or pre-defined when handling different problems before the system 
starts learning?

4. "In principle, every state is potentially reachable from every other state, 
if a logic rule exists between them. Now we use a deep FFNN to represent the 
set of all logic rules." Theoretically speaking, yes, but are inference rules 
between two states are handled continuously or discretely?

5. How interestingness is defined within the system? Why some propositions have 
low interestingness and what is the purpose of having "forgetting mechanism" in 
the addressed model?

6. Experiments or use cases implemented by the addressed model is preferred.

7. References from Wikipedia is not encouraged.

----------------------- REVIEW 2 ---------------------
SCORE: -1 (Weak Reject)

There are a lot of promising statements in the abstract to the paper but there 
is absolutely no justification of this statements in the main text. Some of the 
ideas are looking plausible, but have no theoretical or experimental 
verification. Some of the stetements are simply not correct, e.g. statement 
about Turing completeness of RNNs (they really are but with some additional 
refinement). Some of the statements are self-containing and trivial. Also paper 
lacks of motivation for some of the presented models, e.g. 15, which should be 
a picture (isn't it?). And two more major drawbacks of the paper are its 
organization and appearance.

----------------------- REVIEW 3 ---------------------
SCORE: -2 (Reject)

This paper is about inductive learning in the framework of AGI.
This paper does not contain any introduction and the reader is very quickly a 
bit lost and does not know how to read and understand it.
The form of this paper should be entirely revised.
Then the paper is not easy to read and to follow, as it proposes an unordered 
sequence of paragraphs with different topics and not necessarily related.
At least, it is not indicated by the authors how we should read the paper and 
what is the objective which is followed.
There is no much ore to say, this paper should be totally revised, on the form 
and the content, to be at least readable and then evaluated in good conditions.

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