--- On Sat, 9/20/08, Pei Wang <[EMAIL PROTECTED]> wrote: > Matt, > > I really hope NARS can be simplified, but until you give me the > details, such as how to calculate the truth value in your "converse" > rule, I cannot see how you can do the same things with a simpler > design.
You're right. Given P(A), P(B), and P(A->B) = P(B|A), you could derive P(A|B) using Bayes law. But you can't assume this knowledge is available. > For your original claim that "The brain does not > implement formal > logic", my brief answers are: > > (1) So what? Who said AI must duplicate the brain? Just > because we cannot image another possibility? It doesn't. The problem is that none of the probabilistic logic proposals I have seen address the problem of converting natural language to formal statements. I see this as a language modeling problem that can be addressed using the two fundamental language learning processes, which are learning to associate time-delayed concepts and learning new concepts by clustering in context space. Arithmetic and logic can be solved directly in the language model by learning the rules to convert to formal statements and learning the rules for manipulating the statements as grammar rules, e.g. "I had $5 and spent $2" -> "5 - 2" -> "3". But a better model would deviate from the human model and use an exact formal logic system (such as calculator) when long sequences of steps or lots of variables are required. My vision of AI is more like a language model that knows how to write programs and has a built in computer. Neither component requires probabilistic logic. -- Matt Mahoney, [EMAIL PROTECTED] ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
