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 respondsto 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 | Modify Your Subscription ------------------------------------------- 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
