Skip to main content

2015/2016 Challenge Results

Winner

The winner of the 2015/2016 competition, with 14 wins out of 18, is called Samaritan.

 

Partecipant Teams

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

Team 1: Alphabot

Binary representation of the board using two integers.

Iterative deepening search with alpha-beta pruning.

Multi-threaded idle-time searching.

The heuristic function is based on the value of the player's checkers.

Result achived: 10/18 wins.

Team 2: BotQuixote

State represented as arrays of bytes.

Perform state space search with Negamax algorithm and iterative deepening.

Use a revisited "Pectu-Holban" heuristic function and rely on transposition table to speed up the search.

Idle-time searching.

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

Team members: Ballanti Marcello, Di Vincenzo Marco e Sarti Paolo.

Result achived: 10/18 wins.

Team 3: Samaritan

Board state represented as two integers.

MTD(f) search algorithm with use of alpha-beta pruning and transposition tables.

The heuristic function consider many aspects of the board with different weights. The weights have been defined through genetic algorithms.

Iterative deepening search.

Result achived: 14/18 win.

Team 4: Cogito ergo Expando

Board state represented as an integer array.

Search in the state space with Negamax algorithm.

Transposition table to speed up the search.

Idle-time seatch based on the prediction of opponent move.

Iterative search and static state to improve memory usage.

Result achived: 1/18 wins.

Team 5: Mulinator

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

Team members: Lazzari Nicola and Rossetto Andrea

Result achived: 1/18 wins.

Team 6: TI GUSTA LA MANGUSTA?!

Alpha-beta search with Iterative Deepening.

Heuristic function based on mill possibility of the two players.

Result achived: 8/18 wins.

Team 7: DEEPLELE

Use of the AIMA library.

It performs an alpha-beta search that can be stopped with a timeout.

Parametric heuristic functions that changes according to game phase.

Result achived: 12/18 wins.

Team 8: Cook Iothin

Alpha-beta search with Iterative deepening.

Random choice of the next move during exploration.

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

Team members: Baroncelli Leonardo, Calabria Francesco and Zaini Kevin.

Result achived: 9/18 wins.

Team 9: BarbaMill

Board represented as two integer.

Alpha-beta search with iterative deepening and move sorting.

Idle-time search.

Members: Casadio Alex, Nigro Simone.

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

Result achived: 9/18 wins.

Team 10: La gallina Rosita

Negamax search.

Parametric heuristic function with different weight for each phase.

Use of enumerative instead of strings for the representation of the state.

To avoid memory limits, a single game state is mantained and changed through the search.

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

Team members: Thomopulos Nikos

Result achived: 11/18 wins.

AttachmentSize
risultati15-16.zip74.61 KB