--- On Fri, 12/26/08, Ben Goertzel <[email protected]> wrote: > IMO the test is *too* generic ...
Hopefully this work will lead to general principles of learning and prediction that could be combined with more specific techniques. For example, a common way to compress text is to encode it with one symbol per word and feed the result to a general purpose compressor. Generic compression should improve the back end. My concern is the data is not generic enough. A string has an algorithmic complexity that is independent of language up to a small constant, but in practice that constant (the algorithmic complexity of the compiler) can be much larger than the string. I have not been able to find a good solution to this problem. I realize there are some very simple, Turing-complete systems, such as a 2 state machine with a 3 symbol alphabet, and a 6 state binary machine, as well as various cellular automata (like rule 110). The problem is that programming simple machines often requires long programs to do simple things. For example, it is difficult to find a simple language where the smallest program to output 100 zero bits is shorter than 100 bits. Existing languages and instruction sets tend to be complex and ad-hoc in order to allow programmers to be expressive. -- 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=123753653-47f84b Powered by Listbox: http://www.listbox.com
