Fast & Furious Game Playing : Monte Carlo Drift

A MCTS Algorithm Artificial Intelligence software for Arimaa.


The purpose of this project is to create an Artificial Intelligence software able to play Arimaa against humans or other A.I.s using the Monte Carlo Tree Search algorithm.


Monte Carlo Tree Search Algorithm

Due to the high number of branches (500 times more than chess), it is impossible to explore every possibility.

Using probabilities, random simulations and backtracking, the
Monte Carlo Tree Search Algorithm provides a way to decrease the number of possibilities to be explored.

Tree Parallelisation...

on multicore CPUs.

This software takes advantage of the power provided by the growing popularity of multicore computers.

Each core is working on its own part of the tree, making the search up to 8 times faster !

Root Distribution...

on a set of clusters.

For even more processing power, the algorithm can distribute its work among several machines. Using a Master-Worker strategy, each computer added to the cluster increases the odds of finding an advantageous move.

As each worker has its own copy of the tree, there is but few communications between the machines, thus decreasing the amount of inteference and speeding up the search.
Prateek Bhatnagar - Baptiste Bignon - Mikaïl Demirdelen
Gabriel Prevosto - Dan Seeruttun--Marie - Benoît Viguier

Supervisors: Nikolaos Parlavantzas & Christian Raymond