TY - GEN
T1 - Monte mario
T2 - 16th Genetic and Evolutionary Computation Conference, GECCO 2014
AU - Jacobsen, Emil Juul
AU - Greve, Rasmus
AU - Togelius, Julian
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84905715070&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905715070&partnerID=8YFLogxK
U2 - 10.1145/2576768.2598392
DO - 10.1145/2576768.2598392
M3 - Conference contribution
AN - SCOPUS:84905715070
SN - 9781450326629
T3 - GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
SP - 293
EP - 300
BT - GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
PB - Association for Computing Machinery
Y2 - 12 July 2014 through 16 July 2014
ER -