# Difference between revisions of "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.

## Exercise 1 - data types

### Learning targets

• recapitulate Haskell types (keywords `type` and `data`, product and sum types)
• Helium: equality and show functions (pattern matching)
• Haskell: type classes (`Show`, `Eq`, `deriving`)
• list handling (boards will be represented by lists of lists)

### Tasks

• Define data types that represent boards (`Board`), squares (`Square`), positions (`Pos`), pieces (`Piece`, supported by `PieceColor` and `PieceType`) and game states (`State`).
• Helium: Implement suited eq and show functions.
• Haskell: Define/derive instances of `Show` and `Eq`
• 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, for this purpose define a function `valuePiece` that maps pieces to their values (pawn->1, knight and bishop->3, queen->9, rook->5, king->"infinity"=1000).

## Exercise 2 - move generator

### Learning targets

• list comprehension
• stepwise refinement

## Exercise 3 - gametree generation and minimax algorithm

### Learning targets

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

### 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.