tail
of a functional streamLogicT
- backtracking monad transformer with fair operations and pruning
We present a procedure that picks a uniformly distributed random node from a tree. We traverse the tree only once and we do not know beforehand the number of nodes in the tree. The provably correct algorithm is an instance of a Reservoir sampling.
The procedure is written in a pure functional subset of R5RS Scheme and comes with a correctness proof. We must stress that the proof was developed not after the implementation but along with the implementation. In our experience, thinking about the proof and writing it down notably helped design and code the algorithm. Once the proof was written, the code followed immediately. The code worked on the first try.
comp.lang.scheme
on Tue, 15 Apr 2003 22:17:15 -0700This code demonstrates Dynamic Programming on the problem
of pretty printing a paragraph of text on a printer with fixed-width
fonts. The goal is to tightly arrange a given sequence of n
words within page margins, maximizing overall neatness. To be more precise, we wish to minimize the sum, over all lines
except the last, of the cubes of the number of blank characters at the
end of each line. See the comments in the code for more details.
The algorithm has O(n^2)
time and space
complexities.
word_layout.cc [9K]
Commented C++ source code and sample output, with many
annotations.
Z. Galil, K. Park: A linear-time algorithm for concave one-dimensional dynamic programming
Information Processing Letters, v33, N6, 309-311, 1990.
<http://portal.acm.org/citation.cfm?id=79800>
David Eppstein, livejournal.com user 11011110, pointed out that
the present problem is an instance of concave 1d dynamic programming, which
admits a linear-time solution.
The following two-part article attempts to design the fastest
solution to the problem of finding all subsets of a given size from a
given set. The precise problem is: given a set L
and a number N
, return the set of all subsets of L
of cardinality N
. Sets are represented by
lists. We will be using R5RS Scheme.
In part 1, we start with the mathematical definition of the problem, which leads to a simple, correct, but inefficient solution. We then try to systematically optimize the function until we end up with the fastest function, which is notably faster than the other solutions proposed so far. The final solution is still pure functional. We also demonstrate that the choice of the Scheme interpreter does matter in relative performance of various algorithms.
In part 2, we again start with the mathematical definition of the problem, which leads to a simple, correct, and stunningly efficient solution. The final, so far the fastest solution is still pure functional. The key was to choose the right definition.
In the discussion, Doug Quale presented lazy stream implementations in Haskell and Scheme, and compared them with the above. Eli Barzilay described various memozied versions, which have even better performance. The two USENET threads contain the excellent discussion of the relative merits of memoization and laziness, contributed by Doug Quale and Eli Barzilay. The threads also include many timing comparisons.
Part 1 of the article [plain text file]
It was originally posted as Re: Subsets of a list on the newsgroup comp.lang.scheme
on Sat, 12 Jan 2002 00:52:23 -0800
Part 2 of the article [plain text file]
It was originally posted as The FASTEST subsets function [Was: Subsets of a list] on the newsgroup comp.lang.scheme
on Sat, 12 Jan 2002 00:56:01 -0800
The article is updated with a more optimized solution, which
should perform better when compiled.
Discussion threads of the above titles, comp.lang.scheme
, Jan 9-18, 2002.
<http://google.com/group/comp.lang.scheme/browse_thread/thread/671474460d3e31d8>
<http://google.com/group/comp.lang.scheme/browse_thread/thread/ba04bcb97d8a6c2b>
We describe a concise Haskell solution to the ``Mr.S and Mr.P'' puzzle. We rely on the straightforward encoding of multiple-world semantics of modalities.
The problem was posed by John McCarthy as follows. We
pick two numbers a
and b
, so that a>=b
and both numbers are within the range [2,99]. We give Mr.P
the product a*b
and give Mr.S the sum a+b
.
The following dialog takes place:
a
and b
?
The following Haskell code demonstrates a generic method of encoding facts, and the knowledge about facts, and the knowledge of the knowledge, etc. Incidentally, compared to the notation in McCarthy's paper, the Haskell notation is notably concise.
Chung-chieh Shan commented: ``The basic idea is to think of a set of possible worlds. Corresponding to each person (whose knowledge is being modeled) is a partition of this set of possible worlds; each partition contains one or more worlds that this person cannot distinguish. For someone to know a fact is for all of that person's indistinguishable possible worlds to verify that fact. For Alice to know that Bob doesn't know the weather, is for all of Alice's possible worlds (relative to the real world) to reside within a Bob-partition in which the weather is not consistent across all worlds.''
John McCarthy: Formalization of two Puzzles Involving
Knowledge. 1987.
<http://www-formal.stanford.edu/jmc/puzzles.html>
Mr-S-P.lhs [4K]
Complete literate Haskell98 code. It was first mentioned in the message posted on
Lambda-the-Ultimate on Jan 27, 2003. The present version adds a
straightforward memoization.
Hans P. van Ditmarsch, Ji Ruan and Rineke Verbrugge: Sum and Product in Dynamic Epistemic Logic
Journal of Logic and Computation, 2008, v18, N4, pp.563--588.
The paper discusses at great extent the history of the puzzle, its
modeling in modal `public announcement logic', and solving using
epistemic model checkers.
Inspired by Hans van Ditmarsch's tutorial course on Dynamic Epistemic Logic at NASSLLI 2010, we present a simplistic model-theoretic framework to solve the puzzles like the following:
Anne, Bill and Cath each have a positive natural number written on their foreheads. They can only see the foreheads of others. One of the numbers is the sum of the other two. All the previous is common knowledge. The following truthful conversation takes place:
We encode the statement of the problem as a filter on possible worlds.
The possible worlds consistent with the statement of the problem are
the solutions. `Agent A
does not know
proposition phi
' is interpreted as the statement that for
all worlds consistent with the propositions that A
currently
knows, phi
is true in some worlds but false in the others.
DynEpistemology.hs [10K]
Complete commented Haskell98 code
H.P. van Ditmarsch, W. van der Hoek, and B.P. Kooi: Dynamic Epistemic
Logic and Knowledge Puzzles
Proc. 15th International Conference on Conceptual Structures (ICCS).
LNCS 4604, pp. 45-58, Springer, 2007.
Representing knowledge about knowledge: ``Mr.S and Mr.P'' puzzle
We show how to merge two folds `elementwise' into the
resulting fold. Furthermore, we present a library of potentially
infinite ``lists'' represented as folds (aka streams, aka
success-failure-continuation--based generators). Whereas the standard
Haskell Prelude functions such as map
and take
transform lists, we transform folds. We implement the range of
progressively more complex transformers -- from map
,
filter
, takeWhile
to take
, to
drop
and dropWhile
, and finally, zip
and zipWith
. The standard list API
is also provided.
Emphatically we never convert a stream to a list and so we never use recursion or recursive types. All iterative processing is driven by the fold itself. We only need higher-ranked types, because lists cannot be fully implemented in simply typed lambda-calculus.
The implementation of zip also solves the problem of ``parallel loops''. One can think of a fold as an accumulating loop and realize a nested loop as a nested fold. Representing a parallel loop as a fold is a challenge, answered at the end of the article. This becomes especially interesting in the case of general backtracking computations, or backtracking computations in direct style, with delimited continuations modeling `lists'.
zip-folds.lhs [13K]
Complete literate Haskell code. An earlier version was posted on the Haskell mailing
list on Tue, 11 Oct 2005 17:25:24 -0700 (PDT). That version
implemented zip with the help of a recursive type. The present
version, inspired by a question from Chung-chieh Shan, introduces no
extra data types, no recursion, and rather relies on the already
defined functions to deconstruct a fold. Version 1.6 adds
two examples of surprisingly simple expressions of list
intersperse and Fibonacci in terms of fold.
Beyond Church encoding: Boehm-Berarducci isomorphism of algebraic data types and polymorphic lambda-terms
LogicT
- backtracking monad transformer with fair
operations and pruning
which illustrates the close connection with foldr/build
list-fusion, aka ``short-cut deforestation''. The FR
representation of lists is what one passes to build
.
Predecessor and lists are not representable in
simply typed lambda-calculus
Therefore, higher-rank or recursive/inductive
types are necessary for lists.
Parallel composition of streams: several sources to one sink
Folding over multiple streams using monad transformers
n
sequences. For example(cross-product '((0) (0 1 2 3) (1 2)))should evaluate to
((0 0 1) (0 0 2) (0 1 1) (0 1 2) (0 2 1) (0 2 2) (0 3 1) (0 3 2))The solution is especially elegant if we use the standard (SRFI-1)
append-map
function.comp.lang.scheme
on Thu, 11 Jan 2001 19:59:45 GMTA primitive self-contained C code that computes and prints
out 3^N
very fast. A non-negative integer
exponent N
may be as big as 2000
.
This is an intended solution to a problem presented at the 1995 Programming Contest organized by University of North Texas' Chapter of ACM. The full text of the problem is given in the title comments to the code.
What counts is the overall speed, of computing the result
and converting it to ASCII. And fast the code is: on HP
9000/770/J210, it completes 3^2000
under 0.09 seconds,
whereas bc
takes 0.3 seconds of user time. The present
code uses no multiplications or divisions to compute and print
3^N
.
Computing prime numbers is an important practical task as well as a common example for programming language tutorials. The Eratosthenes sieve is probably the most familiar algorithm for determining prime numbers. Alas, quite many implementations that call themselves Eratosthenes sieve do not actually implement that algorithm. For example, the classic Haskell code
primes = sieve [ 2.. ] where sieve (p:x) = p : sieve [ n | n <- x, n `mod` p > 0 ]is not the Eratosthenes sieve. For one thing, it uses the division operation (or,
mod
). The Eratosthenes sieve specifically
avoids both division and multiplication, which were quite difficult in
old times. Mainly, as Melissa O'Neill explains below, the code
above tests every number for divisibility by all
previously found primes. In contrast, the true Eratosthenes sieve
affects only composite numbers. The prime numbers are `left out'; they
are not checked by division or numeric comparison.
Given below are several implementations of the true Eratosthenes sieve algorithm, in Scheme, Scheme macros, and Haskell. The algorithm is usually formulated in terms of marks and crossing off marks, suggesting the imperative implementation with mutable arrays. The Scheme code follows that suggestion, using two important optimizations kindly described by George Kangas.
Eratosthenes sieve, however, can be implemented purely functionally, as Scheme macros and Haskell code demonstrate. The Haskell implementation is not meant to be efficient -- rather, it is meant to be purely functional, insightful, minimalist, and generalizable to other number sieves, e.g., `lucky numbers'. Like other Haskell algorithms it produces a stream of prime numbers. The Haskell implementation stores only marks signifying the numbers, but never the numbers themselves. Not only the implementation avoids multiplication, division or the remainder operations. We also avoid general addition and number comparison. We rely exclusively on the successor, predecessor and zero comparison. The predecessor can be easily eliminated. Thus the algorithm can be used with Church and Peano numerals, or members of Elliptic rings, where zero comparison and successor take constant time but other arithmetic operations are more involved.
Melissa O'Neill: Re: Genuine Eratosthenes sieve
<http://www.haskell.org/pipermail/haskell-cafe/2007-February/022666.html>
Messages explaining the sieve algorithm and its differences from
impostors; posted on Haskell-Cafe mailing list, February 2007.
Eratosthenes sieve and its optimal implementation [plain text file]
The explanation of the original Eratosthenes sieve and its
optimizations.
The original article was posted as Re: arbitrary precision rationals on a newsgroup comp.lang.scheme
on Tue, 13 Nov 2001 15:07:34 -0800
number-sieve.lhs [4K]
The literate Haskell98 source code for pure functional,
minimalist Eratosthenes and lucky number sieves
The code was originally posted in an article Even better Eratosthenes sieve and lucky numbers on the Haskell-Cafe mailing list on Mon, 12 Feb 2007 18:37:46 -0800 (PST)
A stress test of the syntax-rule macro-expander
Eratosthenes sieve as a syntax-rule macro, to perform
primality test of Church-Peano numerals at macro-expand time
Lucky numbers: another number sieve
<http://mathworld.wolfram.com/LuckyNumber.html>
<http://www.research.att.com/~njas/sequences/A000959>
This site's top page is http://okmij.org/ftp/
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