So, by "discrete reasoning" I think you kind of mean more or less "not neural networks" or I think some people say, or used to say NOT "soft computing" to mean, oh hell!, we aren't really sure how it works, or we can't create what looks like a clear, more or less deterministic program like in the old days etc.... Really, the challenge a lot of people, myself included, have taken up is how to fuse discrete (I simply call it "symbolic", although nn have symbols, typically you don't see them except as input and output) and DL which is such a good way to approach combinatorial explosion.
To me reasoning is mostly conscious, and kind of like the way an expert system chains, logically. The understanding is something else riding kind of below it and less conscious but it has all the common sense rules of reality which constrain the upper level reasoning which I think is logical, like "if car won't start battery is dead" would be the conscious part but the understanding would include such mundane details as "a car has one battery" and "you can see the car but it is in space which is not the same thing as you" and "if you turn around to look at the battery the car is still there" and all such details which lead to an understanding. But understanding is an incredibly tough thing to make a science out of, although I see papers lately and conference topics on it. On 6/20/18, Jim Bromer via AGI <[email protected]> wrote: > I was just reading something about the strong disconnect between our > actions and our thoughts about the principles and reasons we use to > describe why we react the way we do. This may be so, but this does not show > how we come to understand basic ideas about the world. This attempt to make > a nearly total disconnect between reasons and our actual reactions misses > something when it comes to explaining how we know anything, including how > we learn to make decisions about something. One way to get around this > problem is to say that it all takes place in neural networks which are not > open to insight about the details. But there is another explanation which > credits discrete reasoning with the ability to provide insight and > direction and that is we are not able to consciously analyze all the > different events that are occurring at a moment and so we probably are > reacting to many different events which we could discuss as discrete events > if we had the luxury to have them all brought to our conscious attention. > So logic and personal principles are ideals which we can use to examine our > reactions - and our insights - about the what is going on around us but it > is unlikely that we can catalogue all the events that surround us and > (partly) cause us to react the way we do. > > Jim Bromer > > On Wed, Jun 20, 2018 at 6:06 AM, Nanograte Knowledge Technologies via AGI < > [email protected]> wrote: > >> "As Julian Jaynes put it in his iconic book *The Origin of Consciousness >> in the Breakdown of the Bicameral Mind* >> >> Reasoning and logic are to each other as health is to medicine, or — >> better — as conduct is to morality. Reasoning refers to a gamut of >> natural >> thought processes in the everyday world. Logic is how we ought to think >> if >> objective truth is our goal — and the everyday world is very little >> concerned with objective truth. Logic is the science of the justification >> of conclusions we have reached by natural reasoning. My point here is >> that, >> for such natural reasoning to occur, consciousness is not necessary. The >> very reason we need logic at all is because most reasoning is not >> conscious >> at all." >> >> https://cameroncounts.wordpress.com/2010/01/03/mathematics-and-logic/ >> >> >> <https://cameroncounts.wordpress.com/2010/01/03/mathematics-and-logic/> >> Mathematics and logic | Peter Cameron's Blog >> <https://cameroncounts.wordpress.com/2010/01/03/mathematics-and-logic/> >> Apologies: this will be a long post, and there will be more to come. But >> it may be useful to you if you are getting to grips with logic: I have >> tried to keep the overall picture in view. >> cameroncounts.wordpress.com >> >> >> ------------------------------ >> *From:* Jim Bromer via AGI <[email protected]> >> *Sent:* Wednesday, 20 June 2018 12:01 PM >> *To:* AGI >> *Subject:* Re: [agi] Discrete Methods are Not the Same as Logic >> >> Discrete statements are used in programming languages. So a symbol (a >> symbol phrase or sentence) can be used to represent both data and >> programming actions. Discrete Reasoning might be compared to something >> that has the potential to be more like an algorithm. (Of course, >> operational statements may be retained as data which can be run when >> needed) >> For an example of the value of Discrete Methods, let's suppose someone >> wanted more control over a neural network. Trying to look for logic in >> a neural network does not really make all that much sense if you want >> to find relationships between actions on the net and output. Using >> Discrete Methods makes a lot of sense. You might want to try fiddling >> with the weights of some of the nodes as the nn is running. If certain >> effects can be described (or sensed by some algorithm) then describing >> what was done and what effects were observed would be the next step in >> the research. Researchers are not usually able to start with detailed >> knowledge of exactly what is going on. So they need to start with >> descriptions of some actions they took and of what effects were >> observed. If these actions and effects can be categorized in some way >> then the chance that more effective observations will be obtained will >> increase. >> Jim Bromer >> >> >> On Tue, Jun 19, 2018 at 11:12 PM, Mike Archbold via AGI >> <[email protected]> wrote: >> > It sounds like you need both for AI, certainly there is always a place >> > for logic. What's "discrete reasoning"? >> > >> > On 6/18/18, Jim Bromer via AGI <[email protected]> wrote: >> >> I am wondering about how Discrete Reasoning is different than Logic. I >> >> assume that Discrete Reasoning could be described, modelled or >> >> represented by Logic, but as a more practical method, logic would be a >> >> tool to use with Discrete Reasoning rather than as a representational >> >> substrate. >> >> >> >> Discrete Reasons and Discrete Reasoning can have meaning over and >> >> above the True False values of Logic (and the True False Relationships >> >> between combinations of Propositions.) >> >> >> >> Discrete Reasoning can have combinations that do not have a meaning or >> >> which do not have a clear meaning. This is one of the most important >> >> distinctions. >> >> >> >> It can be used in various combinations of hierarchies and/or in >> >> non-hierarchies. >> >> >> >> It can, for the most part, be used more freely with other modelling >> >> methods. >> >> >> >> Discrete Reasoning may be Context Sensitive in ways that produce >> >> ambiguities, both useful and confusing. >> >> >> >> Discrete Reasoning can be Active. So a statement about some subject >> >> might, for one example, suggest that you should change your thinking >> >> about (or representation of) the subject in a way that goes beyond >> >> some explicit propositional description about some object. >> >> >> >> You may be able to show that Logic can be used in a way to allow for >> >> all these effects, but I believe that there is a strong argument for >> >> focusing on Discrete Reasoning, as opposed to Logic, when you are >> >> working directly on AI. >> >> >> >> Jim Bromer >> *Artificial General Intelligence List <https://agi.topicbox.com/latest>* >> / AGI / see discussions <https://agi.topicbox.com/groups/agi> + >> participants <https://agi.topicbox.com/groups/agi/members> + delivery >> options <https://agi.topicbox.com/groups> Permalink >> <https://agi.topicbox.com/groups/agi/Tcc2adcdd20e1add4-M155d4762ea9c7b0f14fefd47> ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tcc2adcdd20e1add4-Mf55a1a349068e2ed778b08fb Delivery options: https://agi.topicbox.com/groups
