# 2014/2015 Challenge Results

## Winner

The winner of the 2014/2015 competition, with 12 wins out of 12, is called DeepMill and is available at Github.

## Partecipant Teams

Any student who has partecipated is free to notify any inaccuracy to Andrea Galassi ( andrea.galassi7 *at* unibo.it )

#### Team 1: negaGlik

Project written in C language.

Uses the NegaScout algorithm to perform a state space search.

Focus on limiting the number of access to memory through static data structures and on limiting the occupied space.

The heuristic function consider many elements, giving a different weight to each one according to the game phase.

Result achived: 10/12 wins.

#### Team 2: Squadra Ginew

Project written in Java language.

Performs a state space search with Iterative Deepening and alpha-beta algorithm.

Members: Aimi NiccolĂ˛, Zama Ramirez Pierlugi, Zanotti Andrea.

The project is available here (courtesy of the authors).

Result achived: 4/12 wins.

#### Team 3: Nexus

Project written in Java language.

Result achived: 1/12 win.

#### Team 4: Duniro

Project written in Java language.

Board representation contains many informations, it is based upon "positions" linked between each other.

Exploit state space search using Limitated Iterative Deepening and alpha-beta algorithm.

The heuristic function is slightly different for each phase and analyzes many factors, among which there are the number of completed and almost completed mills.

Result achived: 4/12 wins.

### Team 5: DeepMill

Project written in Java language.

Compact representation of the state: two binary representation of the board (2 integer of 32 bits) and two integer counters for the number of checkers in players' hands.

A search in the state space is made using Iterative Deepening and the NegaScout algorithm (which is an improvment of alpha-beta search).

Uses a different heuristic function for each phase, considering the number of blocked checkers, the number of Mills present and other factors, focusing on blocking the adversary's checkers.

Uses a Transposition table: during the search, each visited state is saved in an Hash Map which exploit some symmetries of the problem to evaluate the heuristic faster and therefore speed up the search.

The original project is available here (courtesy of the authors).

The updated project is available at Github.

Members: Madonia Tommaso, Di Cesare Alessandro and Franzoni Andrea.

Result achived: 12/12 wins.

#### Team 6: UgoBugo

Project written in Java language.

Uses the NagaScout algorithm to perform the search in the state space

Members: Galassi Andrea.

Result achived: 4/12 wins.

#### Team 7: Unknown

Project written in Java language.

Members: Scarcella Cosimo e Ricci Francesco.

The project is available here (courtesy of the authors).

Result achived: 7/12 wins.