@inproceedings{b4cea88935864b87911b4121e118241c,
title = "Monte mario: Platforming with MCTS",
abstract = "Monte Carlo Tree Search (MCTS) is applied to control the player character in a clone of the popular platform game Su- per Mario Bros. Standard MCTS is applied through search in state space with the goal of moving the furthest to the right as quickly as possible. Despite parameter tuning, only moderate success is reached. Several modifications to the algorithm are then introduced specifically to deal with the behavioural pathologies that were observed. Two of the modifications are to our best knowledge novel. A combination of these modifications is found to lead to almost perfect play on linear levels. Furthermore, when adding noise to the benchmark, MCTS outperforms the best known algorithm for these levels. The analysis and algorithmic innovations in this paper are likely to be useful when applying MCTS to other video games.",
author = "Jacobsen, {Emil Juul} and Rasmus Greve and Julian Togelius",
year = "2014",
doi = "10.1145/2576768.2598392",
language = "English (US)",
isbn = "9781450326629",
series = "GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery",
pages = "293--300",
booktitle = "GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference",
note = "16th Genetic and Evolutionary Computation Conference, GECCO 2014 ; Conference date: 12-07-2014 Through 16-07-2014",
}