On 03/23/2017 11:54 PM, Vishnu Priya wrote:
Thanks Nil. But i have few questions.
1. In real time reasoning, each and every time will you look at the
input data and decide the rules manually?
No. Inference control (IC) would decide what rule(s) to apply. ATM IC is
rather stupid and should to improves over time.
2. Only when the input is in certain form of the rule (or matches with
the rule) which is being chosen, we obtain inferences? (this is how
i understood!)
Correct.
BTW, I have improved and actualized the URE documentation
wiki.opencog.org/w/Unified_rule_engine
I strongly recommend you to read it again (and send feedback if you have
critics so I can improve it).
For instance your question is answered here
http://wiki.opencog.org/w/Unified_rule_engine#Rule_Unification_and_Application
and here
http://wiki.opencog.org/w/Unified_rule_engine#Target_and_Rule_Unification
3. And there exists only such limited number of rules?
The number of rules is indeed limited. It's not clear how big a full PLN
rule set would be. Add to that rule for temporal reasoning, etc. That
could grow big.
4. In the frog.scm,
https://github.com/opencog/atomspace/blob/master/examples/rule-engine/chaining/frog.scm
there are two rules defined. How do these rules are called? I could
not associate these rules with any of the rules
in
https://github.com/opencog/opencog/blob/master/examples/pln/moses-pln-synergy/scm/pln-bc-config.scm
<https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2Fopencog%2Fopencog%2Fblob%2Fmaster%2Fexamples%2Fpln%2Fmoses-pln-synergy%2Fscm%2Fpln-bc-config.scm&sa=D&sntz=1&usg=AFQjCNGFIDFC2krxp9qfasZVzJPbRT7uqg>
?!
Oops, this example is really half baked, if not completely boggus. Have
a look at this instead
https://github.com/opencog/atomspace/blob/master/tests/rule-engine/BackwardChainerUTest.cxxtest#L321
If you wish, as an contributing/learning exercise, you could fix the
frog example based on it.
Nil
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