@Lock:
Thank you for your valuable thoughts. You are describing ANN projects. While I admit ANNs may show some good results towards AGI (yet to be seen what will turn out with super-intelligence), I'm afraid my research led me to the opposite side of the spectrum - symbolic AI that leans towards logic and theorem proving. You know Python now, right? Well, I put my bets on rule-based programming paradigm as a controlled inference process. Rule-based programming may also be used for explicit programming, while entirely controlling each inference step from the programmers side. Roughly, NN is a black box - you train the NN, hoping it will magically connect inputs to outputs. Then to use it, you feed different inputs, yielding different outputs, and it turns out to be a good mach for big enough training corpus. On the other side, rule-based programming is a bit different - you have to explicitly connect different forms of input to different forms of output, and that is what makes it more controllable. Unfortunately, the current state of public research (as far as I'm aware of it) doesn't provide much clue about how to generally describe process of constructing connections between inputs and outputs. We can do it by hand for this or that occasion, but those are specific, not general solutions. I'm also unaware of such a general solution, but I stopped a bit before that. Anyway, to describe my attempts, I think I have clued up a nice way for describing such specific connections. It is nothing new, but just a bit more concise and tidy than I used to see from projects around. I'm not saying ANNs are not working or it isn't a way to go, I'm just saying I invested my time at the different side of AI spectrum. Probably the solution we all want is in some combination between symbolic AI and ANN, so I believe a contribution to each side may be valuable, IMHO.
@Don Patrick
I find your posts well weighed and certainly standing on good feet, as always. I'll carefully consider your criticism, and I think you are helping me to organize my time in more constructive way than I'd do it on my own. Thank you for taking a time to hear me. These days (weeks, months) I plan to finish my Prolog-like concept, and you gave me a good thought food to consider in a meanwhile.