On 8/5/08, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > As noted there, my impression is that PILP could be implemented within OpenCog's PLN backward chainer (currently being ported to OpenCog by Joel Pitt, from the Novamente internal codebase) via writing a special scoring function ...
Yes, I think the inductive search is somewhat similar to backward chaining, except that the steps in the inductive search can *create* rules, whereas in backward chaining you're applying *existing* rules. We need a scoring function, but I have not thought about this yet. I think the hardest part is actually in generating the search tree. You see, in first-order logic, rules can involve many predicates, predicates may have variables as arguments, and the arguments may even have complex terms involving functions. So the combinatorial explosion is severe. The scoring function may provide a "gradient" over the search space, so you suggested to use hill-climbing. But I suspect that such a gradient is not useful during the search, because the search space is discrete and irregular, and the scores probably jump irregularly from node to node. That's why I suspect that hill-climbing is not useful here. Note: I've only studied the ILP problem for a short time. My impressions may be all wrong. We better have an ILP expert here... I need to do some programming to get a better understanding of ILP, but I'm still working on the probabilistic-fuzzy logic... YKY ------------------------------------------- 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=108809214-a0d121 Powered by Listbox: http://www.listbox.com
