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Learning Haskell with Chess

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m (Learning Haskell With Chess moved to Learning Haskell with Chess)

Revision as of 16:26, 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 [1].


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.