Jim, I see what you mean about symbols vs other discrete data and structures etc. I suppose an "unreadable" piece of data could still be converted into symbols, though. An analogy would be that when we input a sound, it is converted to something, a percept... an AGI could input some unreadable data and the converted to a symbolic percept. So by the time the program is running it is symbolic. I suppose my conviction here is that, like I think you are leading up to, is that there still is a huge place for this type of processing....
On 6/21/18, Jim Bromer via AGI <agi@agi.topicbox.com> wrote: > Symbol Based Reasoning is discrete, but a computer can use discrete > data that would not make sense to us so the term symbolic might be > misleading. I am not opposed to weighted reasoning (like neural > networks or Bayesian Networks) and I think reasoning has to use > networks of relations. If weighted networks can be thought of as a > symbolic network then that suggests that symbols may not be discrete > (as different from Neural Networks.) I just think that there is > something missing with DL, and while the Hinton...DL story is > compelling it is not paying out to stronger AI (Near AGI). For > example, I think that symbolic reasoning which is able to change its > categorical bases of reasoning is something that is badly lacking in > Discrete Learning. You don't want your program to forget everything it > has learned just because some doofus tells it to, and you do not want > it to write over the most effective methods it uses to learn just to > deal with some new method of learning. So, that, in my opinion is > where the secret may have been hiding. A program that is capable of > learning something new must be capable of losing its more primitive > learning techniques without wiping out the good stuff that it had > previously acquired. This requires some working wisdom. > I have been thinking about these ideas for a long time but now I feel > that I have a better understanding of how this insight might be used > to point to simple jumping off point. > Jim Bromer > > > On Thu, Jun 21, 2018 at 2:48 AM, Mike Archbold via AGI > <agi@agi.topicbox.com> wrote: >> 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 <agi@agi.topicbox.com> 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 >>> < >>> agi@agi.topicbox.com> 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 <agi@agi.topicbox.com> >>>> *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 >>>> <agi@agi.topicbox.com> 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 <agi@agi.topicbox.com> 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-Mc2801e8605462f99a7ba8da6 Delivery options: https://agi.topicbox.com/groups
