« Lambda counting » : différence entre les versions
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we concentrate on combinatory logic, lambda calculus |
we concentrate on combinatory logic, lambda calculus |
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== Catalan and Motzkin numbers == |
== Lmabert function, Catalan and Motzkin numbers == |
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== combinatory logic == |
== combinatory logic == |
Version du 17 octobre 2008 à 13:47
Introduction
The question is: among programs, what is the probability of having a fixed property.
what kind of program : turing machines, cellular automata, combinatory logic, lambda calculus
what kind of properties : structural (for functional programs), behaviour (SN, weakly normalizable, ...
references to known results on : turing machines, cellular automata
we concentrate on combinatory logic, lambda calculus
Lmabert function, Catalan and Motzkin numbers
combinatory logic
results on combinatory logic
Generality on lambda calculus
what kind of distribution ?
we look only for densities,
for that we need size.
different size for variables: zero, one, binary with optimal size, binary with fixed size, debruijn indices in unary...
we concentrate on the simple one : variable of size zero (probably similar for size one ) more later for other size
generating functions
this does not work (by now) because radius of convergence 0
no known results for the number of terms of size n (denoted )
our results
(the proof of result of section k needs the result of section (k-1))
Upper and lower bounds for
For the lower bound, we will first count the number of lambda-terms of size starting with lambdas and having no other lambda below. This means that the lower part of the term is a binary tree of size with possibility for each leaf. Therefore we have:
upper and lower bounds for number of lambdas in a term of size n
Jakub's trik : at least 1 lambda in head position
at least lambdas in head position and number of lambdas in one path
Remark: (may be 4) can be done directly without 3))
each of the head lambdas really bind "many" occurrences of the variable
every fixed closed term (including the identity !) does not appear in a random term (in fact we have much more than that)
comment : so different situation in combinatory logic and lambda calculus ; the coding uses a big size so need to count variables in a different way
Experiments
results of the experiments we have done
some experiments that have to be done : e.g. density of terms having or big Omega pattern ...
to be done
Upper and lower bounds for with other size for variables especially one, binary with fixed size
Open questions and Future work
.....