2016/2017 Challenge Results


The winner of the 2016/2017 competition, with 9 wins and 5 draws out of 14 matches, is called Akatsuki.

A sum up of the competition results can be found in the attached file "2017end". The detailed results are illustrated in the file "2017results", while the output of each match is available in the file "2017matches".


Partecipant Teams

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

Team 1: MoulinBleu

Negascout algorithm.

State as a 3D byte matrix.

Use of hashtable (Zobrist hashing).

Heuristic: number of open mills and number of checkers.


Team 2: Akatsuki

Heuristic inspired by Petcu–Holban one, but takes into account also the opponent player situation.


Team 3: EUropean Genius

State as a 3x8 matrix. 

The heuristic function changes according to the moment of the game (not only the phase, but also the phases of a phase).


Team 4: Benchwarmers

Iterative Deepening Search.

The heuristic function takes into account the opponent checkers.



Negascout search, use of Peter Brook library.

Iterative Deepening.

Heuristic inspired by Petcu–Holban, but further parameter tuning.


Team 6: Mulino Bianco

State as a long integer (64 bit)

Symmetries considered to limit the possible actions generation.

Iterative Deepening with a different search algorithm for each phase.

Use of transposition table.

Heuristic function parameters tuned using genetic algorithms.


Team 7: Jar Jar

State as 2 integer of 4 bytes.

Use of 4 different heuristics according to the game phase.

Use of Best Node Search.


Team 8: bejoke

Heuristic function based on Fibonacci weights.