# Search Algorithms for Mastermind

## TL;DR

This paper introduces two new algorithms for solving Mastermind, compares them with existing methods, and evaluates their effectiveness in terms of search performance.

## Contribution

The paper presents a novel simulated annealing variant and a maximum expected reduction technique for Mastermind, expanding the toolkit of search strategies.

## Key findings

- MERC outperforms baseline methods in search efficiency
- SA variant shows competitive solution quality
- Comparison highlights strengths and weaknesses of each approach

## Abstract

his paper presents two novel approaches to solving the classic board game mastermind, including a variant of simulated annealing (SA) and a technique we term maximum expected reduction in consistency (MERC). In addition, we compare search results for these algorithms to two baseline search methods: a random, uninformed search and the method of minimizing maximum query partition sets as originally developed by both Donald Knuth and Peter Norvig.