And the problem is not that I can't get up and walk away; it's that I want to keep working here until it's obvious that AI Has Been Solved. Meanwhile, time to take a break from the work documented below. Better respond to SJA and BenG.
1 Sun.10.OCT.2010 -- S-V-O Revisited Yesterday we had not uploaded new MindForth AI code to the Web for three days, and we had backtracked to a slightly earlier codebase of the AI, so we hastened to upload the 9oct10A.F(orth) version with its various enhancements, even though we had begun troubleshooting subject-verb-object (SVO) glitches and had not yet re-established SVO order. To upload the new code with an SVO challenge in it seemed actually like a good way to generate an eagerness to re-engage with a new coding session and to work on SVO revisited, now that great progress has been made on answering bi-directional be-verb based queries, that is, queries about the "YOU" other-concept and about the "I" self-concept. We even feel that S-V-O troubleshooting is much more straightforward and therefore easier than be-verb troubleshooting. So we rename 9oct10A.F as 10oct10A.F and we delve into problems with SVO input and output. 2 Sun.10.OCT.2010 -- Now we have something strange going on with neural inhibition. After we make a few be-verb input statements -- to make sure that the AI handles them correctly -- we type in an SVO statement like "cats eat fish". The AI erroneously answers, "FISH HELPS KIDS", but that glitch is not the main mystery. The main problem is that that the output word "KIDS" is showing up with -31 inhibition, even though the "predflag" variable, at zero, is not indicating a predicate nominative. There must be some left-over, vestigial code that is unwarrantedly inhibiting "KIDS" as a direct object. Oh, in NounPhrase there was indeed such code, with an "OR IF" statement letting either a direct object or a predicate nominative be inhibited. We comment out the "OR IF" code and we reinstated only the code for predicate nominatives, to see what happens. OK. We now have a clear and definite problem. After a few be-verb inputs, when we type in "cats eat fish", the verb 75=HELP has acquired so much stray activation through association from be-verbs, that the AI outputs "FISH HELPS KIDS". Our obvious task here is that somehow we need to work on not letting stray activations build up too mightily. Perhaps we need to make better use of PsiDecay in order to bring stray activations down quite rapidly. Perhaps we need to implement some sort of clean-up routine so that, when a be-verb response has been made to a be-verb input, the AI will go around and make a special effort to damp down the aftermath of stray activations. In general, we are aiming here for a well-tuned AI Mind that activates concepts just enough to generate a logical thought while preventing excess build-up of stray activations. Mentifex -- The un-credentialed AGI guy :-) -- but see: http://www.chatbots.org/ai_zone/viewthread/240/ ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/8660244-d750797a Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=8660244-6e7fb59c Powered by Listbox: http://www.listbox.com
