I agree with this. My opinion is that deliberation is a method where you can bring different kinds of knowledge to bear while trying to better understand a situation. Simpler reactions can be used for habit like responses which are made in reaction to familiar situations. However, I do not think that quick human level (or animal level) responses to complex situations are that feasible for me. I think deliberation will be easier for me.
However, my idea of structured reasoning may allow the program to create simple algorithms (pasting bugless scriptlets together) in such a way that other concepts could have some kind of structured influence on the algorithm (that the program created) as it was running without having it mash up whatever reasoning it was doing. One of my criticisms of being too reliant on funnel reasoning is that useful information will be turned to mash and over cooked when the resultants of different kinds of concepts are combined. This is why I don't see differentiation as a significant problem. I am not going to be mashing analyses together. On the other hand this is why I see complexity as a major problem. Reasoning is going to take place on the basis of a lot of little pieces of information and not the extrusion of a big hopper at the end of a funnel-down decision process. Jim Bromer On Fri, Sep 14, 2012 at 9:51 PM, Piaget Modeler <[email protected]>wrote: > > Jim, > > I'd submit to you that your system have two loops: a reaction loop to > handle familiar recurring situations, > and a deliberation loop to be invoked when habitual or reflex reactions > become insufficient (i.e., fail to > achieve their desired outcomes beyond some threshold of the time--e.g., > failing 30% of the time)). > > > One should seriously take a look at Apple's SIRI since a system like that > may evolve into an AGI if it is > equipped with sufficient back end services (i.e., actions). It has a > reasoner which I presume responds > to user requests in a rule based or case based manner and is tied into > various service providers. > > Cheers! > > ~PM > > ------------------------------ > Date: Fri, 14 Sep 2012 10:06:17 -0400 > Subject: [agi] Simplistic Test of Reason-Based Reasoning > From: [email protected] > To: [email protected] > > > I was wondering if a simple system of reason based reasoning could be used > to start an expanding system of knowledge acquisition. I am not talking > about a human-level AGI program. I am talking about a very simple, very > artificial system to test the viability and the flexibility of the > reason-based reasoning strategy for general learning. > > Reason-based reasoning is just a strategy in which analysis and response > to a situation is based on reasons which the AGI program can access. In > some ways this makes a great deal of sense and it is almost impossible to > understand why this idea has not gained traction in AI discussions. In > another sense this method may be a little more complicated than it seems > because it requires the AGI program to integrate knowledge in ways that I > don't fully understand and it can act as an obstruction to making efficient > decisions and reactions. As our insights become better developed we > become more adept to reacting to the situations for which the insight is > relevant without really thinking of all of the reasons we react the way we > do. This is part of how habits are formed and as best I can tell, part > of the reason that we can react to situations as quickly as we can is > because we can respond effectively to familiar situations without > considering all the reasons why our reactions should work. As we are > learning, our reactions have to be tailored with reasons for making > decisions, but once we learn to recognize a situation we seem to react > without having to focus on all of the reasons why we should make one > decision or another. Obviously this doesn't always work, but it works > well enough most of the time to make it look spectacular from my > perspective. Of course, even with expertise we are still looking for the > reasons we should react in certain ways but our focus seems to be on a more > sophisticated level than it had been at an earlier stage of learning. > > So my question is whether or not reason-based reasoning can be used > effectively in a simplistic system to enable the program to make good > reactions based on what it had learned. But I do not fully understand > how human beings are able to adeptly recognize and react to complicated > situations. > > Analysis and reactions do not only act on some form of output. They can > govern the analysis and reaction modes as well. One issue is how much a > reaction to a particular situation should affect a previously learned > analytical or reactive method. You would not want a system to forget > everything it ever learned in response to a situation but you do want the > program to learn how to improve previously acquired reaction and analytical > methods. One of the issues that I am aware of is that insights are > almost always tied to the generality level of a subject matter and this > idea of a generality level also applies to analytical and reactive methods > as well. For example, a general modification of reactive methods might > be applied temporarily at a global level. This implies that a global > reaction might impact a broad variety of analytical and reactive methods. > This in turn implies that these methods can be modified by other methods > that are not directly embedded into the reaction. I can go on and on > about this but no one has yet shown much interest in my thoughts about this > issue. > > One problem that I do not completely understand is how concepts are > integrated. Reason-based reasoning will help but it does not explain > everything. I am thinking about starting with a primitive artificial > language to make the program work a little like a programming method. > However, > with reason-based reasoning that is able to act on recognition and reaction > methods there is no reason why I could not experiment with language > acquisition. > > This shows that the idea I am talking about is something that is clearly > different from the old narrower AI methods, like expert systems. However, > while I think that this idea could work to enable the program to gain > general knowledge, I am not saying that it would be anything near > human-level reasoning. I am just saying that if a simplistic method > might be able to gain some low level traction for general reasoning in > novel ways then I could have a better base to conduct some experiments into > more complicated problems. I am not sure if I am going to try this or > not but it certainly seems interesting to me right now. > > Jim Bromer > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/19999924-5cfde295> | > Modify <https://www.listbox.com/member/?&;> Your Subscription > <http://www.listbox.com> > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/10561250-164650b2> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
