# Finding optimal strategies in sequential games with the novel selection monad

arXiv: https://arxiv.org/abs/2105.12514 · HTML: https://mlsanity.com/paper/2105.12514/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 26 May 2021.

## Abstract (arXiv)

The recently discovered monad, Tx = Selection (x -> r) -> r, provides an elegant way to finnd optimal strategies in sequential games. During this thesis, a library was developed which provides a set of useful functions using the selection monad to compute optimal games and AIs for sequential games. In order to explore the selection monads ability to support these AI implementations, three example case studies were developed using Haskell: The two-player game Connect Four, a Sudoku solver and a simplified version of Chess. These case studies show how to elegantly implement a game AI. Furthermore, a performance analysis of these case studies was done, identifying the major points where performance can be increased.