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forward chaining - artificial intelligenceimagine we have a set of axioms which we know are true statements regarding the world if we set these to
first-order inference rules -artificial intelligencenow we have a perfect definition of a first-order model isin the same way we may define soundness
variables and quantifiers for first-order models -artificial intelligenceso what do sentences containing variables mean in other words how does first
first-order models - artificial intelligencewe proposed first-order logic like good knowledge representation language rather than propositional logic
and-elimination-introduction rule - artificial intelligenceand-eliminationin english this says that if you know that many things are all true then
propositional inference rules -artificial intelligence equivalence rules are specifically useful because of the vice-versa aspectthat means we can
de morgans lawscontinuing with the relationship between and and or we can also use de morgans law to rearrange sentences involving negation
double negation - artificial intelligencealways parents are correcting their children for the use of double negatives but we have to be very alert
associativity of connectivesin order to tell us brackets are useful when to perform calculations in arithmetic and when to evaluate the truth of
commutatively of connectivesyou will be aware from the fact that some arithmetic operators have a property that it does not matter which way around
equivalences amp rewrite rules - artificial intelligencealong with allowing us to verify trivial theorems tautologies make us able to establish that
truth tables - artificial intelligencein propositional logic where we are limited to expressing sentences where propositions are true or false - we
deductive inferences - artificial intelligencewe have described how knowledge can be represented in first-order logic and how in logic rule-based
logic-based expert systems - artificial intelligenceexpert systems are agents which are programmed to make decisions about real world situations they
search mechanisms in prologwe can utilize this simple prolog program to describe how prolog searchespresidentx - firstnamex georgedubya secondnamex
representation in prolog - logic programs artificial intelligenceif we impose some more constraints on first order logic then we get to a
prolog programming language - artificial intelligencemost of the programming languages are procedural the programmer specifies exactly the correct
appropriate problems for ann learning - artificial intelligence- as we did for decision trees it is essential to know when anns are the correct
back propagation learning routine - aartificial intelligenceas with perceptrons the information in the network is stored in the weights so the
multi-layer network architectures - artificial intelligenceperceptrons have restricted scope in the type of concepts they may learn - they may just
multi-layer artificial neural networks - artificial intelligencenow we can look at more sophisticated anns which are known multi-layer artificial
functions in first-order logic sentences - artificial intelligencefunctions may be thought of as special predicates where we think of all but 1 of
connectives in first-order logic sentences - artificial intelligencewe may string predicates together into a sentence in the same way by utilising
predicates in first-order logic sentences - artificial intelligencethere are predicates first and foremost in first-order logic sentences these