This commit is contained in:
Mark 2023-02-05 21:02:05 -08:00
parent e3e09c9c95
commit 494e91dc98
7 changed files with 574 additions and 612 deletions

View File

@ -1,13 +1,12 @@
% use [nosolutions] flag to hide solutions.
% use [solutions] flag to show solutions.
\documentclass[
solutions,
nosolutions,
singlenumbering
]{../../resources/ormc_handout}
\usepackage{url}
\usepackage{mathtools} % for \coloneqq
\usepackage{subfiles}
% An invisible marker, used to
% draw arrows in equations.
@ -51,11 +50,11 @@
\hfill
\subfile{parts/00 intro}
\subfile{parts/01 combinators}
\subfile{parts/02 boolean}
\subfile{parts/03 numbers}
\subfile{parts/04 recursion}
\subfile{parts/05 challenges}
\input{parts/00 intro}
\input{parts/01 combinators}
\input{parts/02 boolean}
\input{parts/03 numbers}
\input{parts/04 recursion}
\input{parts/05 challenges}
\end{document}

View File

@ -1,29 +1,56 @@
\documentclass[../main.tex]{subfiles}
\section{Definitions}
\generic{$\lm$ Notation:}
$\lm$ notation is used to define functions, and looks like $(\lm ~ \text{input} ~ . ~ \text{output})$. \\
Consider the following statement:
$$
I = \lm a . a
$$
\begin{document}
This tells us that $I$ is a function that takes its input, $a$, to itself. We'll call this the \textit{identity function}. \\
\section{Definitions}
To apply functions, put them next to their inputs. We'll omit the usual parentheses to save space.
\generic{$\lm$ Notation:}
$\lm$ notation is used to define functions, and looks like $(\lm ~ \text{input} ~ . ~ \text{output})$. \\
Consider the following statement:
$$
I = \lm a . a
$$
$$
I ~ \star = (\lm a . a) ~ \star = \star
$$
This tells us that $I$ is a function that takes its input, $a$, to itself. We'll call this the \textit{identity function}. \\
$$
(M~\star) =
(\lm \tzm{b}a. a)~\tzmr{a}\star =
\star
\begin{tikzpicture}[
overlay,
remember picture,
out=225,
in=315,
distance=0.5cm
]
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(a.center) to (b.center);
\end{tikzpicture}
$$
To apply functions, put them next to their inputs. We'll omit the usual parentheses to save space.
Functions are left-associative: If $A$ and $B$ are functions, $(A~B~\star)$ is equivalent to $((A~B)~\star)$. As usual, we'll use parentheses to group terms if we want to override this order: $(A~(B~\star)) \neq (A~B~\star)$ \\
In this handout, all types of parentheses ( $(), [],$ etc ) are equivalent.
$$
I ~ \star = (\lm a . a) ~ \star = \star
$$
\vfill
$$
(M~\star) =
(\lm \tzm{b}a. a)~\tzmr{a}\star =
\star
\generic{$\beta$-Reduction:}
$\beta$-reduction is a fancy name for \say{simplifying an expression.} We've already done it once above.
Let's make another function:
$$
M = \lm f . f f
$$
$M$ takes a function as an input and calls it on itself. What is $(M~I)$?
$$
(M~I) =
((\lm \tzm{b}f.f f)~\tzmr{a}I) =
(I~I) =
((\lm \tzm{d}a.a)~\tzmr{c}I) =
I
\begin{tikzpicture}[
overlay,
remember picture,
@ -33,222 +60,188 @@
]
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(a.center) to (b.center);
\end{tikzpicture}
$$
Functions are left-associative: If $A$ and $B$ are functions, $(A~B~\star)$ is equivalent to $((A~B)~\star)$. As usual, we'll use parentheses to group terms if we want to override this order: $(A~(B~\star)) \neq (A~B~\star)$ \\
In this handout, all types of parentheses ( $(), [],$ etc ) are equivalent.
\vfill
\generic{$\beta$-Reduction:}
$\beta$-reduction is a fancy name for \say{simplifying an expression.} We've already done it once above.
Let's make another function:
$$
M = \lm f . f f
$$
$M$ takes a function as an input and calls it on itself. What is $(M~I)$?
$$
(M~I) =
((\lm \tzm{b}f.f f)~\tzmr{a}I) =
(I~I) =
((\lm \tzm{d}a.a)~\tzmr{c}I) =
I
\begin{tikzpicture}[
overlay,
remember picture,
out=225,
in=315,
distance=0.5cm
]
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(a.center) to (b.center);
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(c.center) to (d.center);
\end{tikzpicture}
$$
We cannot reduce this any further, so we stop. Our expression is now in \textit{$\beta$-normal form}.
\vfill
\pagebreak
\problem{}
Reduce the following expressions:
\begin{itemize}
\item $I~I$
\item $I~I~I$
\item $(\lm a .(a~a~a)) ~ I$
\item $(\lm a . (\lm b . a)) ~ M ~ I$
\end{itemize}
\vfill
\pagebreak
\generic{Currying:}
Lambda functions are only allowed to take one argument, but we can emulate multivariable functions through \say{currying.}
\vspace{1ex}
Before we begin, let's review \textit{function composition}. With \say{normal} functions, composition is written as $(f \circ g)(x) = f(g(x))$. This means \say{$f$ of $g$ of $x$}.
\vspace{1ex}
To demonstrate currying, we'll make a function $C$ in lambda calculus, which takes two functions ($f$ and $g$), an input $x$, and produces $f$ applied to $g$ applied to $x$. \\
In other words, we want a $C$ so that $C~f~g~x = f~(g~x)$
\vspace{1ex}
We'll define this $C$ as follows:
$$
C = \lm f . (\lm g . (\lm x . f(g(x))))
$$
\vspace{1ex}
This looks awfully scary, so let's take this expression apart. \\
C is a function that takes one argument ($f$) and returns a function (underlined):
$$
C = \lm f .(~~\tzm{a} \lm g . (\lm x . f(g(x))) \tzm{b}~~)
\begin{tikzpicture}[
overlay,
remember picture
]
\node[below = 1ex] at (a.center) (aa) {};
\node[below = 1ex] at (b.center) (bb) {};
\path[draw = gray] (aa) to (bb);
\end{tikzpicture}
$$
\vspace{1ex}
The function it returns does the same thing. It takes an argument $g$, and returns \textit{another} function:
$$
C = \lm f . (~~ \lm g . (~~\tzm{a} \lm x . f(g(x)) \tzm{b}~~) ~~)
\begin{tikzpicture}[
overlay,
remember picture
]
\node[below = 1ex] at (a.center) (aa) {};
\node[below = 1ex] at (b.center) (bb) {};
\path[draw = gray] (aa) to (bb);
\end{tikzpicture}
$$
\vspace{1ex}
This last function $\lm x. f(g(x))$ takes one argument, and returns $f(g(x))$. Since this function is inside the previous two, it has access to their arguments, $f$ and $g$.
\vspace{2ex}
So, currying allows us to create multivariable functions by nesting single-variable functions. \\
As you saw above, such expressions can get very long. We'll use a bit of shorthand to make them more palatable. If we have an expression with repeated function definitions, we'll combine their arguments under one $\lm$.
\vspace{1ex}
For example,
$$
C = \lm f . (\lm g . (\lm x . f(g(x))))
$$
will become
$$
C = \lm fgx.(~f(g(x))~)
$$
\vspace{1ex}
This is only notation. \textbf{Curried functions are not multivariable functions!} They must be evaluated one variable at a time, just like their un-curried version. Substituting all curried variables in one go may cause errors, as you'll see below.
\problem{}
Evaluate $C~M~I~\star$ \\
Then, evaluate $C~I~M~I$ \\
\hint{Place parentheses first. Remember, function application is left-associative.}
\vfill
\pagebreak
\definition{$\alpha$-equivalence}
We say two functions are \textit{$\alpha$-equivalent} if they differ only by the names of their variables:
$I = \lm a.a = \lm b.b = \lm \heartsuit . \heartsuit = ...$
\generic{$\alpha$-Conversion:}
Variables inside functions are \say{scoped.} We must take care to keep separate variable separate.
For example, take the functions \\
$A = \lm a b . a$ \\
$B = \lm b . b$
\vspace{2ex}
We could say that $(A~B) = \lm b . (\lm b . b)$, and therefore
$$
((A~B)~I)
= (~ (\lm \tzm{b}b . (\lm b . b))~\tzmr{a}I ~)
= \lm I . I
\begin{tikzpicture}[
overlay,
remember picture,
out=225,
in=315,
distance=0.5cm
]
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(a.center) to (b.center);
(c.center) to (d.center);
\end{tikzpicture}
$$
$$
Which is, of course, incorrect. $\lm I . I$ is not a valid function.
We cannot reduce this any further, so we stop. Our expression is now in \textit{$\beta$-normal form}.
\vspace{2ex}
\vfill
\pagebreak
Notice that both $A$ and $B$ use the input $b$. However, each $b$ is \say{bound} to a different function. The two $b$s are therefore distinct.
\problem{}
Reduce the following expressions:
\begin{itemize}
\item $I~I$
\item $I~I~I$
\item $(\lm a .(a~a~a)) ~ I$
\item $(\lm a . (\lm b . a)) ~ M ~ I$
\end{itemize}
\vspace{2ex}
\vfill
\pagebreak
Let's rewrite $B$ as $\lm c . c$ and try again:
\generic{Currying:}
$$
(A~B) = \lm b . ( \lm c . c) = \lm bc . c
$$
Lambda functions are only allowed to take one argument, but we can emulate multivariable functions through \say{currying.}
Now, we correctly find that $(A~B~I) = (\lm bc . c)~I = \lm c . c = B = I$.
\vspace{1ex}
\problem{}
Let $C = \lm abc.b$ \\
Reduce $(C~a~c~b)$.
Before we begin, let's review \textit{function composition}. With \say{normal} functions, composition is written as $(f \circ g)(x) = f(g(x))$. This means \say{$f$ of $g$ of $x$}.
\begin{solution}
I'll rewrite $(C~a~c~b)$ as $(C~a_1~c_1~b_1)$:
\begin{align*}
C = (\lm abc.b) &= (\lm a.\lm b.\lm c.b) \\
(\lm a.\lm b.\lm c.b)~a_1 &= (\lm b.\lm c.b) \\
(\lm b.\lm c.b)~c_1 &= (\lm c.c_1) \\
(\lm c.c_1)~b_1 &= c_1
\end{align*}
\end{solution}
\vspace{1ex}
\vfill
To demonstrate currying, we'll make a function $C$ in lambda calculus, which takes two functions ($f$ and $g$), an input $x$, and produces $f$ applied to $g$ applied to $x$. \\
\problem{}
Reduce $((\lm a.a)~\lm bc.b)~d~\lm eg.g$
In other words, we want a $C$ so that $C~f~g~x = f~(g~x)$
\begin{solution}
$((\lm a.a)~\lm bc.b)~d~\lm eg.g$ \\
$= (\lm bc.b)~d~\lm eg.g$ \\
$= (\lm c.d)~\lm eg.g$ \\
$= d$
\end{solution}
\vspace{1ex}
\vfill
\pagebreak
We'll define this $C$ as follows:
$$
C = \lm f . (\lm g . (\lm x . f(g(x))))
$$
\end{document}
\vspace{1ex}
This looks awfully scary, so let's take this expression apart. \\
C is a function that takes one argument ($f$) and returns a function (underlined):
$$
C = \lm f .(~~\tzm{a} \lm g . (\lm x . f(g(x))) \tzm{b}~~)
\begin{tikzpicture}[
overlay,
remember picture
]
\node[below = 1ex] at (a.center) (aa) {};
\node[below = 1ex] at (b.center) (bb) {};
\path[draw = gray] (aa) to (bb);
\end{tikzpicture}
$$
\vspace{1ex}
The function it returns does the same thing. It takes an argument $g$, and returns \textit{another} function:
$$
C = \lm f . (~~ \lm g . (~~\tzm{a} \lm x . f(g(x)) \tzm{b}~~) ~~)
\begin{tikzpicture}[
overlay,
remember picture
]
\node[below = 1ex] at (a.center) (aa) {};
\node[below = 1ex] at (b.center) (bb) {};
\path[draw = gray] (aa) to (bb);
\end{tikzpicture}
$$
\vspace{1ex}
This last function $\lm x. f(g(x))$ takes one argument, and returns $f(g(x))$. Since this function is inside the previous two, it has access to their arguments, $f$ and $g$.
\vspace{2ex}
So, currying allows us to create multivariable functions by nesting single-variable functions. \\
As you saw above, such expressions can get very long. We'll use a bit of shorthand to make them more palatable. If we have an expression with repeated function definitions, we'll combine their arguments under one $\lm$.
\vspace{1ex}
For example,
$$
C = \lm f . (\lm g . (\lm x . f(g(x))))
$$
will become
$$
C = \lm fgx.(~f(g(x))~)
$$
\vspace{1ex}
This is only notation. \textbf{Curried functions are not multivariable functions!} They must be evaluated one variable at a time, just like their un-curried version. Substituting all curried variables in one go may cause errors, as you'll see below.
\problem{}
Evaluate $C~M~I~\star$ \\
Then, evaluate $C~I~M~I$ \\
\hint{Place parentheses first. Remember, function application is left-associative.}
\vfill
\pagebreak
\definition{$\alpha$-equivalence}
We say two functions are \textit{$\alpha$-equivalent} if they differ only by the names of their variables:
$I = \lm a.a = \lm b.b = \lm \heartsuit . \heartsuit = ...$
\generic{$\alpha$-Conversion:}
Variables inside functions are \say{scoped.} We must take care to keep separate variable separate.
For example, take the functions \\
$A = \lm a b . a$ \\
$B = \lm b . b$
\vspace{2ex}
We could say that $(A~B) = \lm b . (\lm b . b)$, and therefore
$$
((A~B)~I)
= (~ (\lm \tzm{b}b . (\lm b . b))~\tzmr{a}I ~)
= \lm I . I
\begin{tikzpicture}[
overlay,
remember picture,
out=225,
in=315,
distance=0.5cm
]
\draw[->,gray,shorten >=5pt,shorten <=3pt]
(a.center) to (b.center);
\end{tikzpicture}
$$
Which is, of course, incorrect. $\lm I . I$ is not a valid function.
\vspace{2ex}
Notice that both $A$ and $B$ use the input $b$. However, each $b$ is \say{bound} to a different function. The two $b$s are therefore distinct.
\vspace{2ex}
Let's rewrite $B$ as $\lm c . c$ and try again:
$$
(A~B) = \lm b . ( \lm c . c) = \lm bc . c
$$
Now, we correctly find that $(A~B~I) = (\lm bc . c)~I = \lm c . c = B = I$.
\problem{}
Let $C = \lm abc.b$ \\
Reduce $(C~a~c~b)$.
\begin{solution}
I'll rewrite $(C~a~c~b)$ as $(C~a_1~c_1~b_1)$:
\begin{align*}
C = (\lm abc.b) &= (\lm a.\lm b.\lm c.b) \\
(\lm a.\lm b.\lm c.b)~a_1 &= (\lm b.\lm c.b) \\
(\lm b.\lm c.b)~c_1 &= (\lm c.c_1) \\
(\lm c.c_1)~b_1 &= c_1
\end{align*}
\end{solution}
\vfill
\problem{}
Reduce $((\lm a.a)~\lm bc.b)~d~\lm eg.g$
\begin{solution}
$((\lm a.a)~\lm bc.b)~d~\lm eg.g$ \\
$= (\lm bc.b)~d~\lm eg.g$ \\
$= (\lm c.d)~\lm eg.g$ \\
$= d$
\end{solution}
\vfill
\pagebreak

View File

@ -1,47 +1,39 @@
\documentclass[../main.tex]{subfiles}
\section{Combinators}
\definition{}
A \textit{free variable} in a $\lm$-expression is a variable that isn't bound to any input. \\
For example, $b$ is a free variable in $\lm a. b$. The same is true of $\star$ in any of the previous pages.
\begin{document}
A \textit{combinator} is a function with no free variables.
\section{Combinators}
\definition{The Kestrel}
\definition{}
A \textit{free variable} in a $\lm$-expression is a variable that isn't bound to any input. \\
For example, $b$ is a free variable in $\lm a. b$. The same is true of $\star$ in any of the previous pages.
Notable combinators are often named after birds.\hspace{-0.5ex}\footnotemark{} We've already met a few: \\
The \textit{Idiot}, $I = \lm a.a$ \\
The \textit{Mockingbird}, $M = \lm f.ff$ \\
The \textit{Cardinal}, $C = \lm fgx.(~ f(g(x)) ~)$ \\
A \textit{combinator} is a function with no free variables.
\footnotetext{Raymond Smullyan's \textit{To Mock a Mockingbird} is responsible for this.}
\definition{The Kestrel}
\vspace{2ex}
Notable combinators are often named after birds.\hspace{-0.5ex}\footnotemark{} We've already met a few: \\
The \textit{Idiot}, $I = \lm a.a$ \\
The \textit{Mockingbird}, $M = \lm f.ff$ \\
The \textit{Cardinal}, $C = \lm fgx.(~ f(g(x)) ~)$ \\
Another notable combinator is $K$, the \textit{Kestrel}:
$$
K = \lm ab . a
$$
\problem{}
What does the Kestrel do? Explain in plain English. \\
\hint{What is $(K~\heartsuit~\star)$?}
\footnotetext{Raymond Smullyan's \textit{To Mock a Mockingbird} is responsible for this.}
\vspace{2cm}
\vspace{2ex}
\problem{}
Reduce $(K~I)$ to derive the \textit{Kite}. How does the Kite compare to the Kestrel? \\
We'll call the Kite KI.
Another notable combinator is $K$, the \textit{Kestrel}:
$$
K = \lm ab . a
$$
\problem{}
What does the Kestrel do? Explain in plain English. \\
\hint{What is $(K~\heartsuit~\star)$?}
\begin{solution}
$\text{KI} = \lm ab . b$. \\
\end{solution}
\vspace{2cm}
\problem{}
Reduce $(K~I)$ to derive the \textit{Kite}. How does the Kite compare to the Kestrel? \\
We'll call the Kite KI.
\begin{solution}
$\text{KI} = \lm ab . b$. \\
\end{solution}
\vfill
\pagebreak
\end{document}
\vfill
\pagebreak

View File

@ -1,71 +1,66 @@
\documentclass[../main.tex]{subfiles}
\section{Boolean Algebra}
The Kestrel selects its first argument, and the Kite selects its second. This \say{choosing} behavior is awfully similar to something you may have already seen...
\vspace{1ex}
Let $T = K\phantom{I} = \lm ab . a$ \\
Let $F = KI = \lm ab . b$ \\
\problem{}
Write a function $\text{NOT}$ so that $(\text{NOT} ~ T) = F$ and $(\text{NOT}~F) = T$. \\
\hint{What is $(T~\heartsuit~\star)$? How about $(F~\heartsuit~\star)$?}
\begin{document}
\begin{solution}
$\text{NOT} = \lm a . (a~F~T)$ \\
\end{solution}
\section{Boolean Algebra}
\vfill
The Kestrel selects its first argument, and the Kite selects its second. This \say{choosing} behavior is awfully similar to something you may have already seen...
\problem{}
Write functions $\text{AND}$, $\text{OR}$, and $\text{XOR}$ that satisfy the following table.
\begin{center}
\begin{tabular}{|| c c || c | c | c ||}
\hline
$A$ & $B$ & $(\text{AND}~A~B)$ & $(\text{OR}~A~B)$ & $(\text{XOR}~A~B)$ \\
\hline\hline
F & F & F & F & F \\
\hline
F & T & F & T & T \\
\hline
T & F & F & T & T \\
\hline
T & T & T & T & F \\
\hline
\end{tabular}
\end{center}
\begin{solution}
There's more than one way to do this, of course, but make sure the kids understand how the solutions below work.
\begin{align*}
\text{AND} &= \lm ab . (a~b~F) = \lm ab . aba \\
\text{OR} &= \lm ab . (a~T~b) = \lm ab . aab \\
\text{XOR} &= \lm ab . (a~ (\text{NOT}~b) ~b)
\end{align*}
It may be worth mentioning that OR $= \lm ab.(M~a~b)$ is also a solution.
\end{solution}
\vfill
\problem{}
To complete our boolean algebra, write the boolean equality check EQ. \\
What inputs should it take? What outputs should it produce?
\begin{solution}
$\text{EQ} = \lm ab . [a~(bTF)~(bFT)] = \lm ab . [a~b~(\text{NOT}~b)]$
\vspace{1ex}
Let $T = K\phantom{I} = \lm ab . a$ \\
Let $F = KI = \lm ab . b$ \\
$\text{EQ} = \lm ab . [\text{NOT}~(\text{XOR}~a~b)]$
\end{solution}
\problem{}
Write a function $\text{NOT}$ so that $(\text{NOT} ~ T) = F$ and $(\text{NOT}~F) = T$. \\
\hint{What is $(T~\heartsuit~\star)$? How about $(F~\heartsuit~\star)$?}
\begin{solution}
$\text{NOT} = \lm a . (a~F~T)$ \\
\end{solution}
\vfill
\problem{}
Write functions $\text{AND}$, $\text{OR}$, and $\text{XOR}$ that satisfy the following table.
\begin{center}
\begin{tabular}{|| c c || c | c | c ||}
\hline
$A$ & $B$ & $(\text{AND}~A~B)$ & $(\text{OR}~A~B)$ & $(\text{XOR}~A~B)$ \\
\hline\hline
F & F & F & F & F \\
\hline
F & T & F & T & T \\
\hline
T & F & F & T & T \\
\hline
T & T & T & T & F \\
\hline
\end{tabular}
\end{center}
\begin{solution}
There's more than one way to do this, of course, but make sure the kids understand how the solutions below work.
\begin{align*}
\text{AND} &= \lm ab . (a~b~F) = \lm ab . aba \\
\text{OR} &= \lm ab . (a~T~b) = \lm ab . aab \\
\text{XOR} &= \lm ab . (a~ (\text{NOT}~b) ~b)
\end{align*}
It may be worth mentioning that OR $= \lm ab.(M~a~b)$ is also a solution.
\end{solution}
\problem{}
To complete our boolean algebra, write the boolean equality check EQ. \\
What inputs should it take? What outputs should it produce?
\begin{solution}
$\text{EQ} = \lm ab . [a~(bTF)~(bFT)] = \lm ab . [a~b~(\text{NOT}~b)]$
\vspace{1ex}
$\text{EQ} = \lm ab . [\text{NOT}~(\text{XOR}~a~b)]$
\end{solution}
\vfill
\pagebreak
\end{document}
\vfill
\pagebreak

View File

@ -1,226 +1,220 @@
\documentclass[../main.tex]{subfiles}
\section{Numbers}
\begin{document}
Since the only objects we have in $\lm$-calculus are functions, it's natural to think of quantities as \textit{adverbs} (once, twice, thrice,...) rather than \textit{nouns} (one, two, three ...) \\
\section{Numbers}
\vspace{1ex}
Since the only objects we have in $\lm$-calculus are functions, it's natural to think of quantities as \textit{adverbs} (once, twice, thrice,...) rather than \textit{nouns} (one, two, three ...) \\
We'll start with zero. If our numbers are \textit{once,} \textit{twice,} and \textit{twice}, it may make sense to make zero \textit{don't}. \\
Here's our \textit{don't} function: given a function and an input, don't apply the function to the input.
$$
0 = \lm fa.a
$$
If you look closely, you'll find that $0$ is $\alpha$-equivalent to the false function $F$.
\problem{}
Write $1$, $2$, and $3$. We will call these \textit{Church numerals}.\hspace{-0.5ex}\footnotemark{} \\
\note{\textit{Note:} This problem read aloud is \say{Define \textit{once}, \textit{twice}, and \textit{thrice}.}}
\footnotetext{after Alonzo Church, the inventor of lambda calculus and these numerals. He was Alan Turing's thesis advisor.}
\begin{solution}
$1$ calls a function once on its argument: \\
$1 = \lm fa . (f~a)$.
\vspace{1ex}
We'll start with zero. If our numbers are \textit{once,} \textit{twice,} and \textit{twice}, it may make sense to make zero \textit{don't}. \\
Here's our \textit{don't} function: given a function and an input, don't apply the function to the input.
Naturally, \\
$2 = \lm fa . [~f~(f~a)~]$ \\
$3 = \lm fa . [~f~(f~(f~a))~]$
\vspace{1ex}
The round parentheses are \textit{essential}. Our lambda calculus is left-associative!
\vspace{2ex}
Also, notice that $1$ is very similar to $I$:
$$
0 = \lm fa.a
I~\heartsuit~\star = 1~\heartsuit~\star
$$
If you look closely, you'll find that $0$ is $\alpha$-equivalent to the false function $F$.
\problem{}
Write $1$, $2$, and $3$. We will call these \textit{Church numerals}.\hspace{-0.5ex}\footnotemark{} \\
\note{\textit{Note:} This problem read aloud is \say{Define \textit{once}, \textit{twice}, and \textit{thrice}.}}
Zero is false, and one is the identity. Isn't that wonderful?
\end{solution}
\footnotetext{after Alonzo Church, the inventor of lambda calculus and these numerals. He was Alan Turing's thesis advisor.}
\vfill
\begin{solution}
$1$ calls a function once on its argument: \\
$1 = \lm fa . (f~a)$.
\problem{}
What is $(4~I)~\star$?
\vspace{1ex}
\vfill
Naturally, \\
$2 = \lm fa . [~f~(f~a)~]$ \\
$3 = \lm fa . [~f~(f~(f~a))~]$
\problem{}
What is $(3~NOT~T)$? \\
How about $(8~NOT~F)$?
\vspace{1ex}
\vfill
The round parentheses are \textit{essential}. Our lambda calculus is left-associative!
\pagebreak
\vspace{2ex}
\problem{}
This handout may remind you of Professor Oleg's handout on Peano's axioms. Good. \\
While you're there, recall the tools we used to build the natural numbers: \\
We had a zero element and a \say{successor} operation so that $1 \coloneqq S(0)$, $2 \coloneqq S(1)$, and so on.
Also, notice that $1$ is very similar to $I$:
$$
I~\heartsuit~\star = 1~\heartsuit~\star
$$
\vspace{1ex}
Zero is false, and one is the identity. Isn't that wonderful?
\end{solution}
Create a successor operation for the Church numerals. \\
\hint{A good signature for this function is $\lm nfa$, or more clearly $\lm n.\lm fa$. Do you see why?}
\vfill
\problem{}
What is $(4~I)~\star$?
\vfill
\problem{}
What is $(3~NOT~T)$? \\
How about $(8~NOT~F)$?
\vfill
\pagebreak
\problem{}
This handout may remind you of Professor Oleg's handout on Peano's axioms. Good. \\
While you're there, recall the tools we used to build the natural numbers: \\
We had a zero element and a \say{successor} operation so that $1 \coloneqq S(0)$, $2 \coloneqq S(1)$, and so on.
\begin{solution}
$S = \lm n. [\lm fa . f~(n~f~a)] = \lm nfa . [f~(n~f~a)]$
\vspace{1ex}
Create a successor operation for the Church numerals. \\
\hint{A good signature for this function is $\lm nfa$, or more clearly $\lm n.\lm fa$. Do you see why?}
Do $f$ $n$ times, then do $f$ one more time.
\end{solution}
\begin{solution}
$S = \lm n. [\lm fa . f~(n~f~a)] = \lm nfa . [f~(n~f~a)]$
\vfill
\vspace{1ex}
\problem{}
Verify that $S(0) = 1$ and $S(1) = 2$.
Do $f$ $n$ times, then do $f$ one more time.
\end{solution}
\vfill
\problem{}
Verify that $S(0) = 1$ and $S(1) = 2$.
\vfill
\pagebreak
\vfill
\pagebreak
Assume that only Church numerals will be passed to the functions in the following problems. \\
We make no promises about their output if they're given anything else.
Assume that only Church numerals will be passed to the functions in the following problems. \\
We make no promises about their output if they're given anything else.
\problem{}
Define a function ADD that adds two Church numerals.
\problem{}
Define a function ADD that adds two Church numerals.
\begin{solution}
$\text{ADD} = \lm mn . (m~S~n) = \lm mn . (n~S~m)$ \\
\end{solution}
\begin{solution}
$\text{ADD} = \lm mn . (m~S~n) = \lm mn . (n~S~m)$ \\
\end{solution}
\begin{instructornote}
Defining \say{equivalence} is a bit tricky. The solution above illustrates the problem pretty well.
\begin{instructornote}
Defining \say{equivalence} is a bit tricky. The solution above illustrates the problem pretty well.
\note{Note: The notions of \say{extensional} and \say{intentional} equivalence may be interesting in this context. Do some reading on your own.
}
\note{Note: The notions of \say{extensional} and \say{intentional} equivalence may be interesting in this context. Do some reading on your own.
}
\vspace{4ex}
\vspace{4ex}
These two definitions of ADD are equivalent if we apply them to Church numerals. If we were to apply these two versions of ADD to functions that behave in a different way, we'll most likely get two different results! \\
As a simple example, try applying both versions of ADD to the Kestrel and the Kite.
\vspace{1ex}
To compare functions that aren't $\alpha$-equivalent, we'll need to restrict our domain to functions of a certain form, saying that two functions are equivalent over a certain domain. \\
\end{instructornote}
\vfill
\problem{}
Adding is nice, but we can do better. \\
Design a function MULT that multiplies two numbers. \\
\hint{The easy solution uses ADD, the elegant one doesn't. Find both!}
\begin{solution}
$\text{MULT} = \lm mn . [m~(\text{ADD}~n)~m]$
$\text{MULT} = \lm mnf . [m~(n~f)]$
\end{solution}
\vfill
\pagebreak
\problem{}
Define the functions $Z$ and $NZ$. $Z$ should reduce to $T$ if its input was zero, and $F$ if it wasn't. \\
$NZ$ does the opposite. $Z$ and $NZ$ should look fairly similar.
These two definitions of ADD are equivalent if we apply them to Church numerals. If we were to apply these two versions of ADD to functions that behave in a different way, we'll most likely get two different results! \\
As a simple example, try applying both versions of ADD to the Kestrel and the Kite.
\vspace{1ex}
\begin{solution}
$Z\phantom{N} = \lm n .[n~(\lm a.F)~T]$\\
$NZ = \lm n .[n~(\lm a.T)~F]$
\end{solution}
To compare functions that aren't $\alpha$-equivalent, we'll need to restrict our domain to functions of a certain form, saying that two functions are equivalent over a certain domain. \\
\end{instructornote}
\vfill
\vfill
\problem{}
Adding is nice, but we can do better. \\
Design a function MULT that multiplies two numbers. \\
\hint{The easy solution uses ADD, the elegant one doesn't. Find both!}
\problem{}
Data structures will be useful. Design an expression PAIR that constructs two-value tuples. \\
For example, say $A = \text{PAIR}~1~2$. Then, \\
$(A~T)$ should reduce to $1$ \\
$(A~F)$ should reduce to $2$
\begin{solution}
$\text{MULT} = \lm mn . [m~(\text{ADD}~n)~m]$
\begin{solution}
$\text{PAIR} = \lm ab . \lm i . (i~a~b) = \lm abi.iab$
\end{solution}
$\text{MULT} = \lm mnf . [m~(n~f)]$
\end{solution}
\vfill
From now on, I'll write (PAIR $A$ $B$) as $\langle A,B \rangle$. \\
Like currying, this is only notation. The underlying $\lm$ logic remains the same.
\vfill
\pagebreak
\pagebreak
\problem{}<shiftadd>
Write a function $H$, which we'll call \say{shift and add.} \\
It does exactly what it says on the tin: \\
\problem{}
Define the functions $Z$ and $NZ$. $Z$ should reduce to $T$ if its input was zero, and $F$ if it wasn't. \\
$NZ$ does the opposite. $Z$ and $NZ$ should look fairly similar.
\vspace{1ex}
\begin{solution}
$Z\phantom{N} = \lm n .[n~(\lm a.F)~T]$\\
$NZ = \lm n .[n~(\lm a.T)~F]$
\end{solution}
\vfill
\problem{}
Data structures will be useful. Design an expression PAIR that constructs two-value tuples. \\
For example, say $A = \text{PAIR}~1~2$. Then, \\
$(A~T)$ should reduce to $1$ \\
$(A~F)$ should reduce to $2$
\begin{solution}
$\text{PAIR} = \lm ab . \lm i . (i~a~b) = \lm abi.iab$
\end{solution}
\vfill
From now on, I'll write (PAIR $A$ $B$) as $\langle A,B \rangle$. \\
Like currying, this is only notation. The underlying $\lm$ logic remains the same.
\pagebreak
\problem{}<shiftadd>
Write a function $H$, which we'll call \say{shift and add.} \\
It does exactly what it says on the tin: \\
\vspace{1ex}
Given an input pair, it should shift its right argument left, then add one. \\
$H~\langle 0, 1 \rangle$ should reduce to $\langle 1, 2\rangle$ \\
$H~\langle 1, 2 \rangle$ should reduce to $\langle 2, 3\rangle$ \\
$H~\langle 10, 4 \rangle$ should reduce to $\langle 4, 5\rangle$ \\
\begin{solution}
$H = \lm p . \Bigl\langle~(p~F)~,~S(p~F)~\Bigr\rangle$
\vspace{1ex}
Given an input pair, it should shift its right argument left, then add one. \\
$H~\langle 0, 1 \rangle$ should reduce to $\langle 1, 2\rangle$ \\
$H~\langle 1, 2 \rangle$ should reduce to $\langle 2, 3\rangle$ \\
$H~\langle 10, 4 \rangle$ should reduce to $\langle 4, 5\rangle$ \\
\begin{solution}
$H = \lm p . \Bigl\langle~(p~F)~,~S(p~F)~\Bigr\rangle$
\vspace{1ex}
Note that $H~\langle 0, 0 \rangle$ reduces to $\langle 0, 1 \rangle$
\end{solution}
Note that $H~\langle 0, 0 \rangle$ reduces to $\langle 0, 1 \rangle$
\end{solution}
\vfill
\vfill
\problem{}
Design a function $D$ that un-does $S$. That means \\
$D(1) = 0$, $D(2) = 1$, etc. $D(0)$ should be zero. \\
\hint{$H$ will help you make an elegant solution.}
\problem{}
Design a function $D$ that un-does $S$. That means \\
$D(1) = 0$, $D(2) = 1$, etc. $D(0)$ should be zero. \\
\hint{$H$ will help you make an elegant solution.}
\begin{solution}
$D = \lm n . \Bigl[(~n~H~\langle 0, 0 \rangle~)~T\Bigr]$
\end{solution}
\begin{solution}
$D = \lm n . \Bigl[(~n~H~\langle 0, 0 \rangle~)~T\Bigr]$
\end{solution}
\begin{solution}
Here's a different solution. \\
Can you figure out how it works? \\
\begin{solution}
Here's a different solution. \\
Can you figure out how it works? \\
\vspace{1ex}
\vspace{1ex}
$
D_0 =
\lm p . \Bigl[p~T\Bigr]
\Bigl\langle
F ~,~ p~F
\Bigr\rangle
\Bigl\langle
F
~,~
\bigl\langle
p~F~T ~,~ ( (p~F~T)~(P~F~F) )
\bigr\rangle
\Bigr\rangle
$
$
D_0 =
\lm p . \Bigl[p~T\Bigr]
\Bigl\langle
F ~,~ p~F
\Bigr\rangle
\Bigl\langle
F
~,~
\bigl\langle
p~F~T ~,~ ( (p~F~T)~(P~F~F) )
\bigr\rangle
\Bigr\rangle
$
\vspace{1ex}
\vspace{1ex}
$
D = \lm nfa .
\Bigl(
n D_0 \Bigl\langle T, \langle f, a \rangle \Bigr\rangle
\Bigr)~F~F
$
\end{solution}
$
D = \lm nfa .
\Bigl(
n D_0 \Bigl\langle T, \langle f, a \rangle \Bigr\rangle
\Bigr)~F~F
$
\end{solution}
\vfill
\pagebreak
\end{document}
\vfill
\pagebreak

View File

@ -1,67 +1,61 @@
\documentclass[../main.tex]{subfiles}
\section{Recursion}
\begin{document}
Say we want a function that computes the factorial of a positive integer. Here's one way we could define it:
$$
x! = \begin{cases}
x \times (x-1)! & x \neq 0 \\
1 & x = 0
\end{cases}
$$
\section{Recursion}
We cannot re-create this in lambda notation. Functions in lambda calculus are \textit{anonymous}, which means we can't call them before they've been fully defined.
Say we want a function that computes the factorial of a positive integer. Here's one way we could define it:
$$
x! = \begin{cases}
x \times (x-1)! & x \neq 0 \\
1 & x = 0
\end{cases}
$$
\vspace{1ex}
We cannot re-create this in lambda notation. Functions in lambda calculus are \textit{anonymous}, which means we can't call them before they've been fully defined.
As an example, consider the statement $A = \lm a. A~a$ \\
This means \say{write $(\lm a.A~a)$ whenever you see $A$.} However, $A$ is \textit{inside} what we're rewriting. We'd fall into infinite recursion before even starting our $\beta$-reduction!
\begin{instructornote}
We're talking about recursion, and \textit{computability} isn't far away. At one point or another, it may be good to give the class a precise definition of \say{computable by lambda calculus:}
\vspace{4ex}
Say we have a device that reduces a $\lm$ expression to $\beta$-normal form. We give it an expression, and the machine simplifies it as much as it can and spits out the result. \\
\vspace{1ex}
As an example, consider the statement $A = \lm a. A~a$ \\
This means \say{write $(\lm a.A~a)$ whenever you see $A$.} However, $A$ is \textit{inside} what we're rewriting. We'd fall into infinite recursion before even starting our $\beta$-reduction!
An algorithm is \say{computable by lambda calculus} if we can encode its input in an expression that resolves to the algorithm's output.
\end{instructornote}
\begin{instructornote}
We're talking about recursion, and \textit{computability} isn't far away. At one point or another, it may be good to give the class a precise definition of \say{computable by lambda calculus:}
\problem{}
Write an expression that resolves to itself. \\
\note{Your answer should be short and sweet.}
\vspace{4ex}
\vspace{1ex}
Say we have a device that reduces a $\lm$ expression to $\beta$-normal form. We give it an expression, and the machine simplifies it as much as it can and spits out the result. \\
This expression is often called $\Omega$, after the last letter of the Greek alphabet. \\
$\Omega$ useless on its own, but gives us a starting point for recursion.
\vspace{1ex}
An algorithm is \say{computable by lambda calculus} if we can encode its input in an expression that resolves to the algorithm's output.
\end{instructornote}
\problem{}
Write an expression that resolves to itself. \\
\note{Your answer should be short and sweet.}
\begin{solution}
$\Omega = M~M = (\lm x . xx) (\lm x . xx)$
\vspace{1ex}
This expression is often called $\Omega$, after the last letter of the Greek alphabet. \\
$\Omega$ useless on its own, but gives us a starting point for recursion.
An uninspired mathematician might call the Mockingbird $\omega$, \say{little omega}. \\
\end{solution}
\begin{solution}
$\Omega = M~M = (\lm x . xx) (\lm x . xx)$
\vfill
\vspace{1ex}
\definition{}
This is the \textit{Y-combinator}, easily the most famous $\lm$ expression. \\
You may notice that it's just $\Omega$, put to work.
$$
Y = \lm f . (\lm x . f(x~x))(\lm x . f(x~x))
$$
An uninspired mathematician might call the Mockingbird $\omega$, \say{little omega}. \\
\end{solution}
\problem{}
What does this thing do? \\
Evaluate $Y f$.
\vfill
\definition{}
This is the \textit{Y-combinator}, easily the most famous $\lm$ expression. \\
You may notice that it's just $\Omega$, put to work.
$$
Y = \lm f . (\lm x . f(x~x))(\lm x . f(x~x))
$$
\problem{}
What does this thing do? \\
Evaluate $Y f$.
\vfill
\pagebreak
\end{document}
\vfill
\pagebreak

View File

@ -1,87 +1,82 @@
\documentclass[../main.tex]{subfiles}
\section{Challenges}
\begin{document}
Do \ref{Yfac} first, then finish the rest in any order. \\
Have fun!
\section{Challenges}
\problem{}<Yfac>
Design a recursive factorial function using $Y$. \\
Do \ref{Yfac} first, then finish the rest in any order. \\
Have fun!
\vfill
\problem{}<Yfac>
Design a recursive factorial function using $Y$. \\
\problem{}
Design a non-recursive factorial function. \\
\note{This one is a lot easier than \ref{Yfac}, but I don't think it will help you solve it.}
\vfill
\problem{}
Using pairs, make a \say{list} data structure. Define a GET function, so that $\text{GET}~L~n$ reduces to the nth item in the list. $\text{GET}~L~0$ should give the first item in the list, and $\text{GET}~L~1$, the \textit{second}. \\
Lists have a defined length, so you should be able to tell when you're on the last element.
\problem{}
Design a non-recursive factorial function. \\
\note{This one is a lot easier than \ref{Yfac}, but I don't think it will help you solve it.}
\problem{}
Write POW $a$ $b$, which raises $b$ to the $a$th power.
\problem{}
Using pairs, make a \say{list} data structure. Define a GET function, so that $\text{GET}~L~n$ reduces to the nth item in the list. $\text{GET}~L~0$ should give the first item in the list, and $\text{GET}~L~1$, the \textit{second}. \\
Lists have a defined length, so you should be able to tell when you're on the last element.
\problem{}
Write a MOD $a$ $b$ function that reduces to the remainder of $a \div b$.
\problem{}
Write POW $a$ $b$, which raises $b$ to the $a$th power.
\begin{solution}
\textbf{Factorial with recursion:}
\vspace{3ex}
\problem{}
Write a MOD $a$ $b$ function that reduces to the remainder of $a \div b$.
$\text{FAC} = \lm yn.[Z~n][1][\text{MULT}~n~(y~(\text{D}~n))]$
\begin{solution}
\textbf{Factorial with recursion:}
\vspace{3ex}
\linehack{}
$\text{FAC} = \lm yn.[Z~n][1][\text{MULT}~n~(y~(\text{D}~n))]$
\textbf{Factorial without recursion:}
\vspace{3ex}
\linehack{}
$\text{FAC}_0 = \lm p .
\Bigl\langle~~
\Bigl[D~(p~t)\Bigr]
~,~
\Bigl[\text{MULT}~(p~T)~(p~F)\Bigr]
~~\Bigr\rangle
$
\textbf{Factorial without recursion:}
\vspace{3ex}
\vspace{2ex}
$\text{FAC}_0 = \lm p .
\Bigl\langle~~
\Bigl[D~(p~t)\Bigr]
$
\text{FAC} = \lm n .
\bigl( n~\text{FAC}_0~\langle n, 1 \rangle \bigr)
$
\linehack{}
\textbf{Lists:}
\vspace{3ex}
One possible implementation is
$\Bigl\langle
\langle \text{is last} ~,~ \text{item} \rangle
~,~
\Bigl[\text{MULT}~(p~T)~(p~F)\Bigr]
~~\Bigr\rangle
$
\text{next}...
\Bigr\rangle$, where:
\vspace{2ex}
\vspace{1ex}
$
\text{FAC} = \lm n .
\bigl( n~\text{FAC}_0~\langle n, 1 \rangle \bigr)
$
\say{is last} is a boolean, true iff this is the last item in the list. \\
\say{item} is the thing you're storing \\
\say{next...} is another one of these list fragments. \\
\linehack{}
It doesn't matter what \say{next} is in the last list fragment. A dedicated \say{is last} slot allows us to store ANY function in this list.
\textbf{Lists:}
\vspace{3ex}
\vspace{1ex}
One possible implementation is
$\Bigl\langle
\langle \text{is last} ~,~ \text{item} \rangle
~,~
\text{next}...
\Bigr\rangle$, where:
Here, $\text{GET} = \lm nL.[(n~L~F)~T~F$] \\
\vspace{1ex}
This will break if $n$ is out of range.
\end{solution}
\say{is last} is a boolean, true iff this is the last item in the list. \\
\say{item} is the thing you're storing \\
\say{next...} is another one of these list fragments. \\
\vfill
It doesn't matter what \say{next} is in the last list fragment. A dedicated \say{is last} slot allows us to store ANY function in this list.
\vspace{1ex}
Here, $\text{GET} = \lm nL.[(n~L~F)~T~F$] \\
This will break if $n$ is out of range.
\end{solution}
\vfill
\problem{Bonus}
Play with \textit{Lamb}, an automatic lambda expression evaluator. \\
\url{https://git.betalupi.com/Mark/lamb}
\end{document}
\problem{Bonus}
Play with \textit{Lamb}, an automatic lambda expression evaluator. \\
\url{https://git.betalupi.com/Mark/lamb}