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Learning Haskell with Chess

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This page is about learning Haskell using the board game Chess as a running example. The complete code can be found at [http://www.steffen-mazanek.de/dateien/projekte/hsChess.zip].
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This page is about learning Haskell using the board game Chess as a running example. The complete code can be found at http://www.steffen-mazanek.de/dateien/projekte/hsChess.zip.
   
<h1>Exercise 1 - Data Types</h1>
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==Exercise 1 - data types==
   
<h2>Learning Targets</h2>
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===Learning targets===
<ul>
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*recapitulate Haskell types (keywords type and data, product and sum types)
<li>recapitulate Haskell types (keywords type and data, product and sum types)</li>
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*Helium: define equality functions (pattern matching)
<li>Helium: define equality functions (pattern matching)</li>
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*pretty printing
<li>pretty printing</li>
 
</ul>
 
   
<h2>Tasks</h2>
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===Tasks===
<ul>
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*Define data types that represent boards (<hask>Board</hask>), squares (<hask>Square</hask>), positions (<hask>Pos</hask>), pieces (<hask>Piece</hask>) and game states (<hask>State</hask>).
<li>Define data types that represent boards (Board), squares (Square), positions (Pos), pieces (Piece) and game states (State).</li>
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*Helium: Implement suited eq-functions.
<li>Helium: Implement suited eq-functions.</li>
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*Implement a function <hask>prettyBoard::Board->String</hask>, that transforms a board into a clearly arranged string representation (human readable :-)). Support this function with auxiliary functions that pretty print pieces, squares, ...
<li>Implement a function prettyBoard::Board->String, that transforms a board into a clearly arranged string representation (human readable :-)). Support this function with auxiliary functions that pretty print pieces, squares, ...</li>
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*Define the initial board (<hask>initialBoard::Board</hask>), test prettyBoard with initialBoard.
<li>Define the initial board (initialBoard::Board), test prettyBoard with initialBoard.</li>
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*Implement a simple evaluation function <hask>evalBoard::Board->Int</hask> as the difference of material on board (values: Pawn->1, Knight and Bishop->3, Queen->9, Rook->6, King->"infinity"=1000).
<li>Implement a simple evaluation function evalBoard::Board->Int as the difference of material on board (values: Pawn->1, Knight and Bishop->3, Queen->9, Rook->6, King->"infinity"=1000).</li>
 
</ul>
 
   
<h1>Exercise 2 - Move Generator</h1>
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==Exercise 2 - move generator==
<h2>Learning Targets</h2>
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===Learning targets===
<ul>
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*list comprehension
<li>list comprehension</li>
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*stepwise refinement
<li>stepwise refinement</li>
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===Tasks===
</ul>
 
<h2>Tasks</h2>
 
   
<h1>Exercise 3 - Gametree Generation and Minimax Algorithm</h1>
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==Exercise 3 - gametree generation and minimax algorithm==
<h2>Learning Targets</h2>
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===Learning targets===
<ul>
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*break code in modules
<li>break code in modules</li>
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*complexity
<li>complexity</li>
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*recursive data structures -> recursive algorithms
<li>recursive data structures -> recursive algorithms</li>
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</ul>
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===Tasks===
<h2>Tasks</h2>
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*Define a data type that represents a game tree (<hask>GameTree</hask>).
<ul>
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*Roughly estimate the number of nodes of the gametree with depth 4.
<li>Define a data type that represents a game tree (GameTree).</li>
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*Define a function <hask>play::Gametree->Int</hask>, that computes the value of a given game tree using the minimax Algorithm.
<li>Roughly estimate the number of nodes of the gametree with depth 4.</li>
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*Implement the function <hask>doMove::State->State</hask>, that choses the (best) next state.
<li>Define a function play::Gametree->Int, that computes the value of a given game tree using the minimax Algorithm.</li>
 
<li>Implement the function doMove::State->State, that choses the (best) next state.</li>
 
</ul>
 

Revision as of 16:34, 18 March 2007

This page is about learning Haskell using the board game Chess as a running example. The complete code can be found at http://www.steffen-mazanek.de/dateien/projekte/hsChess.zip.

Contents

1 Exercise 1 - data types

1.1 Learning targets

  • recapitulate Haskell types (keywords type and data, product and sum types)
  • Helium: define equality functions (pattern matching)
  • pretty printing

1.2 Tasks

  • Define data types that represent boards (
    Board
    ), squares (
    Square
    ), positions (
    Pos
    ), pieces (
    Piece
    ) and game states (
    State
    ).
  • Helium: Implement suited eq-functions.
  • Implement a function
    prettyBoard::Board->String
    , that transforms a board into a clearly arranged string representation (human readable :-)). Support this function with auxiliary functions that pretty print pieces, squares, ...
  • Define the initial board (
    initialBoard::Board
    ), test prettyBoard with initialBoard.
  • Implement a simple evaluation function
    evalBoard::Board->Int
    as the difference of material on board (values: Pawn->1, Knight and Bishop->3, Queen->9, Rook->6, King->"infinity"=1000).

2 Exercise 2 - move generator

2.1 Learning targets

  • list comprehension
  • stepwise refinement

2.2 Tasks

3 Exercise 3 - gametree generation and minimax algorithm

3.1 Learning targets

  • break code in modules
  • complexity
  • recursive data structures -> recursive algorithms

3.2 Tasks

  • Define a data type that represents a game tree (
    GameTree
    ).
  • Roughly estimate the number of nodes of the gametree with depth 4.
  • Define a function
    play::Gametree->Int
    , that computes the value of a given game tree using the minimax Algorithm.
  • Implement the function
    doMove::State->State
    , that choses the (best) next state.