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• The implication addition:
Γ
⇒ Γ ⇒ ⊃
(4)
A B
;
A B
if B is deductible from an assumptions set and from an assumption A , then the rule A B is deductible
from the system. The connexity notion is present here as we need the fact that B is deductible from A
to be able to add the rule A B , which means that a path between A and B must be present.
• The implication retraction or modus ponens:
ERROR -Please resubmit formula
(5)
if A is deductible from the system and if A is the premise of a system deductible rule, then the conclu-
sion of this rule is directly deductible from the system.
• The rule called reductio ad absurdum :
ERROR -Please resubmit formula
(6)
if B can be deductible AND falsifiable from the system including A , then A is falsified. This axiom
introduce the conflict management dealt lately.
FR interpretation axioms. Interpretation axioms are not in the first order since they introduce clauses
and multiple values (like the 'unknown' one). Our syntax will be in the first order, but the interpretation
is not monotonous.
give knowledge ( a )⇒ A True ;
any knowledge supplied by the 'teacher' is considered as true.
give inFormation ( a )≡ A ε[ True , False , Unknown ];
any supplied information is a formula interpretable in a multi-valued space.
give explanation ( a )≡( give -i nformation ( p ),a↔p);
any explanation consists in supplying a right formula, equivalent to the formula A that has to be
explained.
Tutored Learning Situations And Goals. Our learning situation brings into play two characters: A
'teacher' and a 'student'. The learning initiative may come from either the 'teacher' or the 'student'.
Teacher's initiative. In this case, we'll speak about a lesson, i.e. the 'teacher' will try to make the
'student' understanding a set of unknown knowledge.
For our artificial agents, we transpose this situation in the following goal:
1. Enriching the student's KB with new data
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