# Difference between revisions of "AI"

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== People == |
== People == |
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If interested in contributing to or monitoring this project, please put your name, nickname (if applicable - e.g., if you talk on #haskell), and email address so we can keep each other up-to-date. |
If interested in contributing to or monitoring this project, please put your name, nickname (if applicable - e.g., if you talk on #haskell), and email address so we can keep each other up-to-date. |
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+ | Yuriy Pitomets (netsu) <pitometsu at gmail> |
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+ | |||

+ | Mark Wong-VanHaren (marklar) <markwvh at gmail> |
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Andrew Wagner (chessguy) <wagner dot andrew at gmail> |
Andrew Wagner (chessguy) <wagner dot andrew at gmail> |
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Adam Wyner (Lawman) <adam dot wyner dot info> |
Adam Wyner (Lawman) <adam dot wyner dot info> |
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− | Allan Erskine (thedatabase) <allan dot erskine at gmail> |
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Dave Tapley (DukeDave) <dukedave at gmail> |
Dave Tapley (DukeDave) <dukedave at gmail> |
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Lloyd Allison <lloyd dot allison at infotech dot monash dot edu dot au> |
Lloyd Allison <lloyd dot allison at infotech dot monash dot edu dot au> |
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+ | |||

+ | Jim Geovedi <jim at geovedi dot com> |
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Paul Berg (Procyon) <procyon at procyondevelopments dot com> |
Paul Berg (Procyon) <procyon at procyondevelopments dot com> |
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Ricardo Honorato-Zimmer (_rata_) <rikardo dot horo at gmail dot com> |
Ricardo Honorato-Zimmer (_rata_) <rikardo dot horo at gmail dot com> |
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+ | Raphael Javaux (RaphaelJ) <raphaeljavaux at gmail dot com> |
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+ | Mahmut Bulut (vertexclique) <mahmutbulut0 at gmail dot com> (ML, natural language processing, swarming intelligence) |
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+ | Mike Izbicki <mike at izbicki.me> |
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+ | Chris Taylor (crntaylor) <crntaylor at gmail> |
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+ | Libor Wagner <wagnelib at cmp dot felk dot cvut dot cz> |
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+ | Florian Grunert <fgrunert ätt uni-osnabrueck dot de> |
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+ | Chad Scherrer <chad (dot) scherrer (at) gmail> (Parallel learning algrorithms, L1 regularization, Bayesian inference) |
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+ | Ant Al'Thor R. <ant (at) theixo (dot) com> (AI Interest & Business) |
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== Ideas == |
== Ideas == |
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If there are things that should be included in the project, but you're not sure where it should go, place it here! I'll start with: |
If there are things that should be included in the project, but you're not sure where it should go, place it here! I'll start with: |
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− | * http://catenova.org/~awagner/Simplifier |
+ | * http://catenova.org/~awagner/Simplifier (broken link) |

**This was given to me by Alfonso Acosta (mentioned recently on haskell-cafe) |
**This was given to me by Alfonso Acosta (mentioned recently on haskell-cafe) |
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− | *http://catenova.org/~awagner/GPLib |
+ | *http://catenova.org/~awagner/GPLib (broken link) |

**[[GPLib]] is a work in progress by yours truly, hopefully a future framework for genetic algorithms in haskell. |
**[[GPLib]] is a work in progress by yours truly, hopefully a future framework for genetic algorithms in haskell. |
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Easy-to-use work-in-progress neural network library, by [[User:AlpMestan|Alp Mestan]] and Chaddaï Fouché : |
Easy-to-use work-in-progress neural network library, by [[User:AlpMestan|Alp Mestan]] and Chaddaï Fouché : |
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*http://github.com/alpmestan/HNN/tree/master |
*http://github.com/alpmestan/HNN/tree/master |
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+ | Implementation of some of the algorithms in Russell and Norvig's "Artificial Intelligence: A Modern Approach", by [[User:Crntaylor|Chris Taylor]]: |
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+ | *https://github.com/chris-taylor/aima-haskell |
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== Proposed Module Hierarchy == |
== Proposed Module Hierarchy == |
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**AI.Logic |
**AI.Logic |
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**AI.Planning |
**AI.Planning |
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+ | ***AI.Planning.Swarm |
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**AI.Probabilistic |
**AI.Probabilistic |
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**AI.Learning |
**AI.Learning |
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== External links == |
== External links == |
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+ | * [http://hackage.haskell.org/packages/archive/pkg-list.html#cat:ai Packages at Hackage, marked AI] |
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* [https://patch-tag.com/r/alpmestan/hasklab/wiki/ HaskLab Wiki] |
* [https://patch-tag.com/r/alpmestan/hasklab/wiki/ HaskLab Wiki] |
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* [http://projects.haskell.org/cgi-bin/mailman/listinfo/hasklab The HaskLab mailing-list] |
* [http://projects.haskell.org/cgi-bin/mailman/listinfo/hasklab The HaskLab mailing-list] |
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* [http://projects.haskell.org/pipermail/hasklab/ The HaskLab Archives] (mailing-list archive) |
* [http://projects.haskell.org/pipermail/hasklab/ The HaskLab Archives] (mailing-list archive) |
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+ | * [http://okmij.org/ftp/Haskell/#memo-off Preventing memoization in (AI) search problems] |
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* [http://jpmoresmau.blogspot.com/2010/09/digit-recognition-with-neural-network.html Digit recognition with a neural network. First attempt!] (Blog article) |
* [http://jpmoresmau.blogspot.com/2010/09/digit-recognition-with-neural-network.html Digit recognition with a neural network. First attempt!] (Blog article) |
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* [http://jpmoresmau.blogspot.com/2010/09/haskell-neural-network-plugging-space.html Haskell Neural Network: plugging a space leak] (Blog article) |
* [http://jpmoresmau.blogspot.com/2010/09/haskell-neural-network-plugging-space.html Haskell Neural Network: plugging a space leak] (Blog article) |
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+ | * [http://www.ki.informatik.uni-frankfurt.de/research/HCAR.html Further Reading] |
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+ | * [https://github.com/smichal/hs-logic hs-logic]; logic programming in Haskell (software on github) |

## Latest revision as of 08:26, 1 December 2018

## Introduction

This is the home for the Haskell AI Strike Force! Here we will collect code, problems, papers, ideas, and people for putting together a flexible AI toolkit in Haskell.

## People

If interested in contributing to or monitoring this project, please put your name, nickname (if applicable - e.g., if you talk on #haskell), and email address so we can keep each other up-to-date.

Yuriy Pitomets (netsu) <pitometsu at gmail>

Mark Wong-VanHaren (marklar) <markwvh at gmail>

Andrew Wagner (chessguy) <wagner dot andrew at gmail>

Bryan Green (shevek) <dbryan dot green at gmail>

Ricardo Herrmann <rherrmann at gmail>

Dan Doel (dolio) <dan dot doel at gmail>

Chung-chieh Shan (ccshan) <ccshan at cs dot rutgers dot edu>

Adam Wyner (Lawman) <adam dot wyner dot info>

Dave Tapley (DukeDave) <dukedave at gmail>

Lloyd Allison <lloyd dot allison at infotech dot monash dot edu dot au>

Jim Geovedi <jim at geovedi dot com>

Paul Berg (Procyon) <procyon at procyondevelopments dot com>

Eric Kow (kowey) <eric dot kow at gmail> [watching on the sidelines]

Charles Blundell <blundellc at gmail>

Mathew Mills (mathewm) <mathewmills (at) gmail (dot) com>

Jason Morton (inverselimit) <jason.morton at gmail>

Jiri Hysek (dvekravy) <xhysek02 at stud dot fit dot vutbr dot cz> [NN, EA]

Shahbaz Chaudhary <shahbazc at gmail> [interested in GP]

Hans van Thiel <hthiel dot char á zonnet tot nl> [automated rule discovery, author of the Emping data mining utility]

Alp Mestanogullari (Alpounet) <alp (at) mestan (dot) fr> [machine learning mainly]

Chris Pettitt (cpettitt) <cpettitt at gmail>

Nathaniel Neitzke (nneitzke) <nightski at gmail>

Ricardo Honorato-Zimmer (_rata_) <rikardo dot horo at gmail dot com>

Raphael Javaux (RaphaelJ) <raphaeljavaux at gmail dot com>

Mahmut Bulut (vertexclique) <mahmutbulut0 at gmail dot com> (ML, natural language processing, swarming intelligence)

Mike Izbicki <mike at izbicki.me>

Chris Taylor (crntaylor) <crntaylor at gmail>

Libor Wagner <wagnelib at cmp dot felk dot cvut dot cz>

Florian Grunert <fgrunert ätt uni-osnabrueck dot de>

Chad Scherrer <chad (dot) scherrer (at) gmail> (Parallel learning algrorithms, L1 regularization, Bayesian inference)

Ant Al'Thor R. <ant (at) theixo (dot) com> (AI Interest & Business)

## Ideas

- In short, parts of this project can range from established ideas to new syntheses. ccshan: The high level of domain-specific abstraction that Haskell enables is ideal for AI, because AI programs are often "meta": we need to model agents who model the world, and sometimes to model agents who model agents who model the world, etc. In particular, monads are a good way to structure and solve decision processes, as I've started to explore as part of a course on computational modeling that I'm teaching. Given that Haskell is a good language for modular interpreters and compilers, it would also be nice to create and refactor in Haskell an implementation of a rational programming language like Avi Pfeffer's IBAL -- not only is probability distribution a monad, I just realized that a certain kind of variable elimination is simply garbage collection in a call-by-need language!

## Things that need a home

If there are things that should be included in the project, but you're not sure where it should go, place it here! I'll start with:

- http://catenova.org/~awagner/Simplifier (broken link)
- This was given to me by Alfonso Acosta (mentioned recently on haskell-cafe)

- http://catenova.org/~awagner/GPLib (broken link)
- GPLib is a work in progress by yours truly, hopefully a future framework for genetic algorithms in haskell.

I've proposed a machine learning library for this year's Google Summer of Code. [1] There has been a few interested (and seemingly well qualified) students, too. I'm not sure if it qualifes as "AI", but if you are interested in this project (as a potential student, mentor, or just...well, interested), please add yourself to the above link, and/or get in touch with me at <ketil at malde dot org>. --Ketil 07:46, 26 March 2007 (UTC)

Martin Erwig's probabilistic functional programming (PFP) project, including an implementation of the probability monad:

Culmination of some recent posts about the probability monad on Random Hacks (including a darcs repository):

sigfpe's coverage and highly algebraic view of the probability monad in Haskell:

Two links I found today that are interesting:

Polytypic unification - unification seems particularly useful for AI tasks (at least natural language stuff)... wouldn't be nice to have a generic library that does it for you?

Easy-to-use work-in-progress neural network library, by Alp Mestan and Chaddaï Fouché :

Implementation of some of the algorithms in Russell and Norvig's "Artificial Intelligence: A Modern Approach", by Chris Taylor:

## Proposed Module Hierarchy

- AI
- AI.Searching
- AI.Searching.Evolutionary

- AI.Logic
- AI.Planning
- AI.Planning.Swarm

- AI.Probabilistic
- AI.Learning
- AI.Learning.Kernel
- AI.Learning.NeuralNet

- AI.Classification
- AI.Classification.ExpertSystem

- AI.Communication

- AI.Searching

## Proposed sample format for a wiki page on a topic or sub-topic

**AI/Logic/Fuzzy**

The slashes show that Logic is a subpage of AI and Fuzzy is a subpage of AI/Logic. MediaWiki will then generate links back up the chain of pages. (Try the links to see)

- Fuzzy logic is blah blah...
- Sub-topics:
- Trivial fuzzy logic in Haskell
- Type 2 fuzzy logic

- Links to existing literature:
- General
- My first fuzzy logic book

- Specific to functional programming / Haskell
- Fun with fuzzy functions

- General
- Typical problems:
- Problem 1: blah blah blah
- Problem 2: blah blah blah

- List of people involved in the area
- Me
- Someone else

- Body
- List of goals
- Progress being made on them
- Code and documentation.

## Current sub-pages

## External links

- Packages at Hackage, marked AI
- HaskLab Wiki
- The HaskLab mailing-list
- The HaskLab Archives (mailing-list archive)
- Preventing memoization in (AI) search problems
- Digit recognition with a neural network. First attempt! (Blog article)
- Haskell Neural Network: plugging a space leak (Blog article)
- Further Reading
- hs-logic; logic programming in Haskell (software on github)