On Sat, Apr 12, 2014 at 4:49 PM, Anastasios Tsiolakidis <[email protected]>wrote:
> Disclaimer: the answer is probably several hours or days of googling away, > just trying to save time here. > > I haven't looked into (non probabilistic) inference engines for a long > time, and it looks like the landscape has changed. I consider them > indispensable for game-like domains (including physics), and I would like > to hear about the performance and subtleties of the new breed. I am working > towards general game playing set-ups, which I've mentioned before as a kind > of AGI drosophila. > May not answer your question, but boolean inference can be relaxed into probabilistic inference with interval probabilities, and that becomes a linear programming problem (with linear constraints on probabilities). The latter can be solved in polynomial time. Probabilistic inference is actually more desirable than boolean inference, as far as AGI is concerned. So the fixation on the NP hardness of boolean inference may be unnecessary. On the other hand, probabilistic inference may offer a route to tackle the P=?NP question. As for boolean inference, I am not aware that the landscape has changed drastically (as far as new techniques are concerned, but some new software may have emerged). The key issue here is to choose the kind of logic, for example whether you want propositional logic, description logic (as used by Semantic Web technologies), first order logic, or higher order logic. The state-of-the-art engines for each kind of logic are constantly improving, but seems to be slowly =) ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
